INVESTIGATION OF EFFECT OF CUTTING PARAMETERS AND … Thesis Full...iii DECLARATION I declare that...

INVESTIGATION OF EFFECT OF CUTTING

PARAMETERS AND TOOL NOSE RADIUS ON

CUTTING FORCES AND SURFACE ROUGHNESS IN

FINISH HARD TURNING OF AISI D2 STEEL WITH

CBN TOOL

A Thesis submitted to Gujarat Technological University

for the Award of

Doctor of Philosophy

in

Mechanical Engineering

By

Vallabhbhai Dahyabhai Patel

Enrollment No.129990919013

under supervision of

Dr. Anishkumar H. Gandhi

GUJARAT TECHNOLOGICAL UNIVERSITY

AHMEDABAD

[June-2018]

i

INVESTIGATION OF EFFECT OF CUTTING

PARAMETERS AND TOOL NOSE RADIUS ON

CUTTING FORCES AND SURFACE ROUGHNESS IN

FINISH HARD TURNING OF AISI D2 STEEL WITH

CBN TOOL

A Thesis submitted to Gujarat Technological University

for the Award of

Doctor of Philosophy

in

Mechanical Engineering

By

Vallabhbhai Dahyabhai Patel

Enrollment No.129990919013

under supervision of

Dr. Anishkumar H. Gandhi


AHMEDABAD

[June-2018]

ii

© Vallabhbhai Dahyabhai Patel

iii

DECLARATION

I declare that the thesis entitled “Investigation of effect of cutting parameters and tool

nose radius on cutting forces and surface roughness in finish hard turning of AISI D2

steel with CBN tool” submitted by me for the degree of Doctor of Philosophy is the record

of research work carried out by me during the period from October-2012 to June- 2018

under the supervision of Dr. Anishkumar. H. Gandhi and his has not formed the basis for

the award of any degree, diploma, associateship, fellowship, titles in this or any other

University or other institution of higher learning.

I further declare that the material obtained from other sources has been duly acknowledged

in the thesis. I shall be solely responsible for any plagiarism or other irregularities, if

noticed in the thesis.

Signature of the Research Scholar: Date: ………………..

Name of Research Scholar: Vallabhbhai Dahyabhai Patel

Place: Ahmedabad

iv

CERTIFICATE

I certify that the work incorporated in the thesis title as Investigation of effect of cutting

parameters and tool nose radius on cutting forces and surface roughness in finish

hard turning of AISI D2 steel with CBN tool submitted by Vallabhbhai Dahyabhai

Patel was carried out by the candidate under my supervision/guidance. To the best of my

knowledge: (i) the candidate has not submitted the same research work to any other

institution for any degree/diploma, Associateship, Fellowship or other similar titles (ii)

the thesis submitted is a record of original research work done by the Research Scholar

during the period of study under my supervision, and (iii) the thesis represents

independent research work on the part of the Research Scholar.

Signature of Supervisor: Date: ……………….

Name of Supervisor: Dr. Anishkumar H. Gandhi

Place: Ahmedabad

v

Originality Report Certificate

It is certified that PhD Thesis titled “Investigation of effect of cutting parameters and

tool nose radius on cutting forces and surface roughness in finish hard turning of

AISI D2 steel with CBN tool” by Mr. Vallabhbhai Dahyabhai Patel has been examined

by us. We undertake the following:

a. Thesis has significant new work / knowledge as compared already published or

are under consideration to be published elsewhere. No sentence, equation,

diagram, table, paragraph or section has been copied verbatim from previous

work unless it is placed under quotation marks and duly referenced.

b. The work presented is original and own work of the author (i.e. there is no

plagiarism). No ideas, processes, results or words of others have been

presented as Author own work.

c. There is no fabrication of data or results which have been compiled /

analyzed.

d. There is no falsification by manipulating research materials, equipment or

processes, or changing or omitting data or results such that the research is not

accurately represented in the research record.

e. The thesis has been checked using https://turnitin.com (copy of originality

report attached) and found within limits as per GTU Plagiarism Policy and

instructions issued from time to time (i.e. permitted similarity index

<=25%).

Signature of the Research Scholar: Date: ….…………..…


Place: Ahmedabad

Signature of Supervisor: Date: ………………...


Place: Ahmedabad

vii

PhD THESIS Non-Exclusive License to


In consideration of being a PhD Research Scholar at GTU and in the interests of the

facilitation of research at GTU and elsewhere, I, Vallabhbhai Dahyabhai Patel having

Enrollment No.129990919013 hereby grant a non-exclusive, royalty free and perpetual

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g) If third party copyrighted material was included in my thesis for which, under the terms

of the Copyright Act, written permission from the copyright owners is required, I have

obtained such permission from the copyright owners to do the acts mentioned in

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h) I retain copyright ownership and moral rights in my thesis, and may deal with the

copyright in my thesis, in any way consistent with rights granted by me to my

University in this non-exclusive license.

viii

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exclusive license.

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all policy matters related to authorship and plagiarism.

Signature of the Research Scholar: Date: ….…………..…


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Seal:

ix

THESIS APPROVAL FORM

The viva-voce of the PhD Thesis submitted by Shri Vallabhbhai Dahyabhai Patel

(Enrollment No.129990919013) entitled Investigation of effect of cutting parameters

and tool nose radius on cutting forces and surface roughness in finish hard turning of

AISI D2 steel with CBN tool was conducted on …………………….………… (day and

date) at Gujarat Technological University.

(Please tick any one of the following option)

The performance of the candidate was satisfactory. We recommend that

he/she be awarded the PhD degree.

Any further modifications in research work recommended by the panel after 3

months from the date of first viva-voce upon request of the Supervisor or

request of Independent Research Scholar after which viva-voce can be re-

conducted by the same panel again.

(briefly specify the modifications suggested by the panel)

The performance of the candidate was unsatisfactory. We recommend that

he/she should not be awarded the PhD degree.

(The panel must give justifications for rejecting the research work)

Name and Signature of Supervisor with Seal

1) (External Examiner 1) Name and Signature



x

ABSTRACT

Because of its excellent wear and abrasion properties, AISI D2 steel is widely used as a

material for bearing races, forming dies, punches, forming rolls, etc. Understanding of the

mechanics of oblique turning of hardened materials is important to industries

manufacturing components like bearings, dies and tools. This research describes

investigation of effect of cutting parameters (cutting speed, feed), tool geometries (tool

nose radius) on cutting forces (cutting force, radial force and axial force) and surface

roughness of AISI D2 steel using cubic boron nitride (CBN) tool. Experiments were

conducted based on full factorial design of experiment. Results shows influence of

different cutting conditions on cutting forces and surface roughness. Forces in axial, radial

and cutting directions vary with the different values of cutting speed, feed and nose radius

at constant depth of cut during hard turning. Initially, force model is developed based on

cutting parameters (i.e. cutting speed and feed) and tool nose radius and further it is

extended by considering progressive flank wear. Empirical model of cutting forces shows

best fits with cutting conditions (i.e. cutting speed and feed) and tool geometries (i.e. tool

nose radius, inclination angle and rake angle). Experimental observation shows that feed

is most significant parameter affecting cutting force, radial force and axial force followed

by nose radius and cutting speed. Cutting forces are linearly proportional to feed and nose

radius whereas, it is inversely proportional to cutting speed. A linear exponential model of

surface roughness shows simultaneous effect of cutting speed, feed and nose radius. Feed

contributes significantly to surface roughness than tool nose radius and cutting speed.

Empirical models of forces and surface roughness are validated with new set of

experiments and found to be with reasonable accuracy of prediction within limits of

cutting parameters and tool geometry considered.

xi

ACKNOWLEDGEMENT

I would like to take an opportunity to express my sincere gratitude who have contributed

to this research work and supported me during this journey.

Firstly, I am extremely grateful to my honorable Supervisor Dr. Anishkumar H.

Gandhi, for his continuous guidance, motivation, encouragement and support for

throughout my research work. His guidance helped me in all the time of research and

writing of this thesis, I could not have imagined having a better advisor and mentor for

my research work.

Besides my advisor, I would like to appreciate to my Doctoral Progress Committee

Members Dr. H. K. Raval, Professor, SVNIT, Surat and Dr. D. I. Lalwani, Associate

Professor, SVNIT, Surat for their rigorous examinations and precious suggestion during

my research. Their valuable suggestions and constructive criticisms from time to time

enabled me to complete my work successfully.

I am thankful to Dr, Akshai Aggarwal, Ex. Vice Chancellor, Dr. Navin Sheth, Vice

Chancellor, Shri J. C. Lilani, Registrar and all staff members of PhD Section, GTU.

I would also like to acknowledge guidance and support provided for experimental work by

Mr. I M Hakim, Turner, ITI, Gandhinagar. I would also thankful to Mr. J. D. Patel and

other staffs of workshop instructors of L D R P Institute of Technology and Research,

Gandhinagar, for their valuable support.

Finally, I would like to thanks my father Mr. Dahyabhai Patel and my mother Mrs.

Shantaben Patel for supporting me spiritually during the hard time of this journey. I

would also like to thank my beloved wife Falguni Patel, my son Jils and my daughter

Navya for their unconditional love and moral support.

xii

Table of Content

CHAPTER - 1 Introduction ..................................................................................................... 1

1.1 Overview. .............................................................................................................................. 1

1.2 Hardened workpiece materials and their specific applications ............................................. 2

1.3 Cutting tools used in hard turning......................................................................................... 3

1.4 Cutting conditions, orientation of three dimensional forces, surface roughness and wear

of cutting tool pertaining to machining of hardened materials ............................ 4

1.5 Organization of thesis ........................................................................................................... 7

References…. ..... ……………………………………………………………………………….9

CHAPTER - 2 Literature review .......................................................................................... 10

2.1 Introduction ......................................................................................................................... 10

2.2 Literature on surface roughness of hardened materials ...................................................... 10

2.3 Literature on cutting forces in hard turning ........................................................................ 12

2.4 Literature on tool wear ........................................................................................................ 14

2.5 Literature on development of models of crater wear, flank wear and cutting forces

during turning of hardened materials ................................................................. 19

2.5.1 Literature on modeling of tool wear .......................................................... 19

2.5.2 Literature on analytical modeling of cutting forces .................................. 23

2.6 Findings of literature review ............................................................................................... 28

2.7 Definition of the problem ................................................................................................... 29

2.8 Objectives and scope of study ............................................................................................ 29

2.9 Significance of Study .......................................................................................................... 29

2.10 Research Methodology ..................................................................................................... 31

References…. ... ……………………………………………………………………………….32

CHAPTER - 3 Design of experiment and experimental work ............................................ 36

3.1 Overview. ............................................................................................................................ 36

3.2 Design of experiment .......................................................................................................... 36

xiii

3.3 Experimental work .............................................................................................................. 38

3.3.1 Workpiece ................................................................................................. 38

3.3.2 Cutting tools .............................................................................................. 40

3.3.3 Machine tool .............................................................................................. 41

3.3.4 Surface roughness tester ............................................................................ 42

3.3.5 Tool maker’s microscope for tool wear measurement .............................. 43

3.3.6 Lathe tool dynamometer for measurement of cutting forces .................... 43

3.3.7 Experimental procedure ............................................................................ 44

CHAPTER - 4 Results and discussion .................................................................................. 50

4.1 Overview. ............................................................................................................................ 50

4.2 Experimental results based on various cutting conditions .................................................. 50

4.2.1 Percentage contribution of cutting variables on cutting forces ................. 53

4.3 Influence of cutting conditions on surface roughness ........................................................ 55

4.3.1 Percentage contribution of cutting variables on surface roughness .......... 57

4.4 Tool flank wear at optimum cutting condition ................................................................... 58

References…. ... ……………………………………………………………………………….64

CHAPTER - 5 Model development of three dimensional forces and surface roughness

for hard turning ................................................................................................ 65

5.1 Overview. ............................................................................................................................ 65

5.2 Modeling of cutting forces .................................................................................................. 65

5.2.1 Modeling of cutting forces based on cutting conditions ........................... 66

5.2.2 Modeling of forces considering progressive flank wear of tool ................ 71

5.2.3 Evaluation of total cutting forces and its comparison with predicted

values….. ............................................................................................................ 74

5.3 Modeling of surface roughness ........................................................................................... 76

5.3.1 Modeling of surface roughness based on cutting conditions and

geometry………………………..……… ........................................................... 77

5.3.2 Determination of constants and validation of surface roughness model ... 79

xiv

References…. …………………………………………………………………………………81

CHAPTER - 6 Conclusions and future scope ...................................................................... 83

6.1 Conclusions ......................................................................................................................... 83

6.2 Future scope ........................................................................................................................ 85

Appendices… .. ……………………………………………………………………………….86

List of publications .................................................................................................................. 90

xv

List of Abbreviation

Pa : Hardness of the abrasive particle

Pt : Tool hardness

T : Average temperature

KQ : Constant related with activation energy for diffusion

Kabrasion : Process related dimensionless abrasive wear coefficient

Kadhesion : Process related adhesive wear coefficient

Kdiff : Process related diffusive wear coefficient

α, αn : Rake/chamfer angle, taken as a positive value for simplicity

γ : Clearance angle

D : Coefficient of diffusion

σ, : Normal shear stress

τs : Shear stress in the shear plane

KT : Tool crater wear depth

n : Dimensionless constant

R : Radius of the tool crater arc

F : Friction force

αe : Effective rake angle

Φe : Shear plane angle, angle between the shear plane and cutting

velocity

i : Inclination angle

β : Friction angle

t1 : Depth of cut/ undeform chip thickness

b : Width of cut

N : Normal force

FH : Principal component of the cutting force

Ft : Thrust force

Vs : Sliding velocity

Ψ : Apex angle of the stagnation zone

k : Material shear flow stress

xvi

θ : Slip line angle

Cs : Side cutting edge angle

ηc : Chip flow angle

Fwcutting, Fwaxial,

Fwradial : Forces due to wear in cutting, axial and radial direction

P1 , P2 , P3 : Forces in cutting, axial, and radial directions

Kn, Kf : Cutting pressure coefficients

Acutting : Cutting cross sectional area

* : Equivalent pertaining angles (e.g. i*= equivalent inclination angle)

Fr : Radial force (N)

Fa : Axial force (N)

Fc : Cutting force (N)

d : Depth of cut (mm)

v : Cutting speed (m/min)

f : Feed (mm/rev)

r : Tool nose radius (mm)

Vb : Tool flank wear length (mm)

Fcw : Force in the cutting direction due to flank wear (N)

Faw : Force in the axial direction due to flank wear (N)

Frw : Force in the radial direction due to flank wear (N)

δFcw : Cutting force component due to wear (N)

δFarw : Resultant wear force component of Fcw and Faw (N)

τw : Shear stress along the flank face (N/mm2)

σw : Normal stress along the flank face (N/mm2)

a0, a1, a2, a3 : Constants depend on radial force and cutting conditions

b0, b1, b2, b3 : Constants depend on axial force and cutting conditions

c0, c1, c2, c3 : Constants depend on cutting force and cutting conditions

Fct : Total cutting force in cutting direction (N)

Fat : Total axial force in feed direction (N)

Frt : Total radial force in radial direction (N)

Ra exp : Experimental value of average surface roughness of machined part

(μm)

Ra pred : Average surface roughness prediction based on all possible factors

(μm)

xvii

Ra vfr : Average surface roughness based on v, f, and r (μm)

c0,c1,c2, c3 : Constants corresponding to cutting conditions and tool geometry

xviii

List of Figures

FIGURE 1.1: Atoms of boron nitride changes from hexagonal to cubic structure .................... 4

FIGURE 1.2: Direction of cutting force, radial force and axial force on cutting tool insert ..... 5

FIGURE 1.3: Different wear phenomenon on single point cutting tool .................................... 7

FIGURE 2.1: Geometrical nomenclature of crater wear of CBN tool used in turning of

hard materials ..................................................................................................... 22

FIGURE 2.2: Material removal concept based on extended Lee and Shaffer’s model using

negative rake angle tool ...................................................................................... 25

FIGURE 2.3: Orientation of cutting forces based on progressive wear of flank face of tool

in hard turning .................................................................................................... 27

FIGURE 2.4: Flow chart of applied research methodology ................................................... 32

FIGURE 3.1: (a) Detailed drawing of workpiece (AISI D2 steel) to perform full factorial

design of experiments (all dimensions are in mm) ............................................ 40

(b) Detailed drawing of workpiece (AISI D2 steel) for flank wear

measurement at optimum cuttingconditions (all dimensions are in mm) .......... 40

FIGURE 3.2: CBN cutting tool insert of 0.4, 0.8 and 1.2 mm nose radius .............................. 41

FIGURE 3.3: Work piece material AISI D2 steel after heat treatment .................................... 44

FIGURE 3.4: Flow diagram of complete experimental work .................................................. 45

FIGURE 3.5: Prefinal size of AISI D2 steel round bar before starting of experiment ............ 45

FIGURE 3.6: Finish hard turning at different cutting conditions ............................................ 46

FIGURE 3.7: Experiment set up of lathe tool dynamometer ................................................... 46

FIGURE 3.8: Measurement of surface roughness with the help of surface roughness tester

SJ210 .................................................................................................................. 47

FIGURE 3.9: Turning up to 65 mm cutting length for flank wear measurement .................... 47

FIGURE3.10:Flank wear measurement with suitable fixture using Tool maker’s

microscope……. .......................................................................................... …..48

xix

FIGURE 4.1: Influence of feed (f) and nose radius of tool (r) on axial (Fa), radial (Fr) and

cutting (Fc) force at cutting speed (v) = 80 m/min and depth of cut (d) = 0.2

mm ...................................................................................................................... 52

FIGURE 4.2: Influence of feed (f) and tool nose radius (r) on axial (Fa), radial (Fr) and


mm ...................................................................................................................... 52

FIGURE 4.3: Influence of feed (f) and tool nose radius (r) on axial (Fa), radial (Fr) and


mm ...................................................................................................................... 53

FIGURE 4.4: Effect of cutting speed (v) and feed (f) on surface roughness at tool nose

radius (r) = 0.4 mm and depth of cut (d) = 0.2 mm ........................................... 55

FIGURE 4.5: Effect of cutting speed (v) and feed (f) on surface roughness at tool nose


FIGURE 4.6: Effect of cutting speed (v) and feed (f) on surface roughness (Ra) at tool nose


FIGURE 4.7: Effect of flank wear on cutting forces at optimum cutting conditions (cutting

speed (v) = 152 m/min, feed (f) =0.04 mm/rev and tool nose radius (r) = 1.2

mm) .................................................................................................................... 60

FIGURE 4.8: Effect of flank wear on surface roughness at optimum cutting conditions

(cutting speed (v) = 152 m/min, feed (f) =0.04 mm/rev and tool nose radius

(r) = 1.2 mm) ...................................................................................................... 60

FIGURE 4.9: Correlation of surface roughness and cutting forces at optimum cutting

conditions (cutting speed (v) = 152 m/min, feed (f) =0.04 mm/rev and tool

nose radius (r) = 1.2 mm) ................................................................................... 61

FIGURE 4.10: Effect of flank wear on resultant cutting forces at optimum cutting


nose radius (r) = 1.2 mm) as per Table 4.6 ........................................................ 62

FIGURE 4.11: Effect of resultant cutting forces on surface roughness at optimum cutting


nose radius (r) = 1.2 mm) as per Table 4.6 ........................................................ 62

xx

FIGURE 5.1: Experimental and predicted value of cutting force based on different cutting

conditions (cutting speed (v), feed (f) and nose radius (r) as reported in Table

5.2) ...................................................................................................................... 69

FIGURE 5.2: Experimental and predicted value of radial force based on different cutting


5.2) ...................................................................................................................... 70

FIGURE 5.3: Experimental and predicted value of axial force based on different cutting


5.2) ...................................................................................................................... 70

FIGURE 5.4: Tool flank wear geometry; (a) cutting force component in z direction, (b)

effective flank and nose wear, (c) resultant force component of x and y

direction .............................................................................................................. 72

FIGURE 5.5: Cutting forces in cutting (Fcw), radial (Frw) and axial (Faw) directions due to

tool flank wear evaluated based on progressive flank wear modeling ............... 74

FIGURE 5.6: Comparison of total cutting force (Fct) considering flank wear (Vb) ................. 75

FIGURE 5.7: Comparison of total radial force (Frt) considering flank wear (Vb) ................... 75

FIGURE 5.8: Comparison of total axial force (Fat) considering flank wear (Vb) .................... 76

FIGURE 5.9: Experimental and predicted value of surface roughness based on different

cutting conditions (cutting speed (v), feed (f) and nose radius (r) as

reported in Table 5.4) ........................................................................................ 80

xxi

List of Tables

TABLE 1.1: Comparisons of hard turning and grinding ............................................................ 2

TABLE 2.1: Different cutting conditions used in various literatures during hard turning ....... 18

TABLE 3.1: Values of input parameters for turning experiments ........................................... 37

TABLE 3.2: Experimental design using full factorial design of experiment ........................... 37

TABLE 3.3: Chemical composition of AISI D2 steel in percentage ........................................ 39

TABLE 3.4: Physical properties of AISI D2 steel .................................................................... 39

TABLE 3.5: Specifications of lathe (NH 22 HMT make) ........................................................ 41

TABLE 3.6: Specifications of surface roughness tester SJ210 ................................................ 42

TABLE 3.7: Specifications of tool maker’s microscope .......................................................... 43

TABLE 3.8: Specifications of lathe tool dynamometer ........................................................... 43

TABLE 4.1: Experimental readings of axial (Fa), radial (Fr) and cutting (Fc) force and

surface roughness (Ra) ....................................................................................... 51

TABLE 4.2: Percentage contribution of nose radius, cutting speed and feed attributes to

cutting force ........................................................................................................ 54


radial force .......................................................................................................... 54


axial force ........................................................................................................... 54


surface roughness ............................................................................................... 58

TABLE 4.6: Experimental readings of tool flank wear, surface roughness and cutting

forces at optimum cutting conditions ................................................................. 59

TABLE 5.1: Model constants evaluated using 27 experimental readings as per Table 4.1 ..... 68

TABLE 5.2: Experimental value of cutting (Fc exp), radial (Fr exp) and axial (Fa exp) force at

different cutting conditions ................................................................................ 68

TABLE 5.3: Model constants evaluated based on 27 experimental results as per Table 4.1 ... 79

xxii

TABLE 5.4: Experimental values of surface roughness (Ra exp) using different sets of

cutting conditions ............................................................................................... 79

xxiii

List of Appendices

Appendix A : Calculation of percentage contribution of variable cutting and geometry

parameters on cutting forces .............................................................................. 86

Appendix B : Calculation of percentage contribution of variable cutting and geometry

parameters on surface roughness ........................................................................ 88

Overview

1

CHAPTER – 1

Introduction

In this chapter, concept of hard turning is defined. Benefits of hard turning over grinding

are discussed. Application of various hardened steel material grades especially hardened

AISI D2 steel is discussed. Various tool materials for turning of hardened steel material

grades along with their characteristics are discussed. Various machining parameters, tool

geometry parameters and machining conditions affecting mechanism of cutting are

discussed.

1.1 Overview

Turning of steel materials with hardness value above 45 HRC (Rockwell hardness) is

defined as hard turning. Hard turning with single point cutting tool is very complex when

hardness of workpiece is in the range of 55-68 HRC [1-3]. Hardness of material, tools

which are used for cutting and mechanism of chip formation differ the hard turning from

conventional turning. Hard turning is an economic and an efficient alternative to grinding

which converts raw materials into desired shape. If complex components could be

manufactured using hard turning, production costs could be decreased up to 70 % [4].

Surface quality can be achieved up to the level of grinding in hard turning. Quality

improvement, cost reduction and reduce setup duration is very challenging in today‘s

market. This scenario enforces the manufacturer to increase quality of product and

efficiency. Turning of materials can be effectively done after heat treatment is the major

benefit over traditional techniques like finish grinding operation [5]. Benefits of hard

turning over grinding are shown in Table 1.1.

Highly precise parts, made up of advanced hardened alloys used in aerospace industries are

manufactured using metal removal processes. Hard components like roller bearings, dies,

tools, automotive parts like crank pins and hydraulic parts have been widely manufactured

using hard turning technology. Cutting fluid and lubricants are not used in hard turning,

thus storage, maintaining and disposal of cutting fluid is eliminated and it may favor the

Ch. 1 Introduction

2

health of machine operators [2]. It has other benefits such as flexibility, higher material

removal rate and reduced machining time [6].

TABLE 1.1

Comparisons of hard turning and grinding [6]

Though hard turning is advantageous over grinding process, it also possesses certain

limitations as described. For example, residual stresses are produced beneath the surface of

turned part due to high temperature and high pressure induces during metal removing.

Also, tool wear is critical phenomenon which deteriorates the surface finish of machined

part.

1.2 Hardened Workpiece Materials and Their Specific Applications

Different workpiece materials are hardened up to 68 HRC and used for specific

applications. Recently, various industries pertaining to machining of hardened materials

commonly use different steels like AISI H11, AISI H13, AISI D2, AISI D3, AISI M2,

AISI M42, AISI T1, AISI T4 and AISI T5. AISI D2 steel is known as high carbon, high

chromium steel. It is used for manufacturing of various parts due to its specific properties

like high strength, high fatigue strength and high wear resistance. Machinability and

toughness of AISI D2 steel are considered to be low [6]. Its specific applications in

industries are mentioned below:

Tools for heavy duty hot forming process like dies, mandrels etc.

Extrusion of rod and tube

Tools for hot impact extrusion

Various tools for production of nuts, screws, rivets, bolts and hollow bodies

Various dies of press machine

Sr. No. Description Hard turning Grinding

1 Rate of metal removal 150 – 1500 mm3/min 10 - 60 mm

3/min

2 Flexibility Very flexible Low flexibility

3 Cutting process Stable Tendency to jerk

4 Accuracy 0.2 micron Ra Better than 0.2 micron Ra

5 Pre-machining duration Less More

6 Effect on atmosphere Material removal

without cutting fluid

Material removal with cutting

fluid

Cutting tools used in hard turning

3

Different dies of casting

Dies of forming process

Cutting blades of hot shearing

1.3 Cutting Tools Used in Hard Turning

All hard machining operations require specific cutting tool materials which can withstand

against the critical conditions produced during machining. Performance of cutting tools are

affected due to tool wear (crater and flank wear), thrust and temperature developed during

machining. Some special characteristics require for tool materials are high wear resistance,

high hardness and chemical stability [7]. Various tool materials like cemented tungsten

carbide, ceramics, cubic boron nitride (CBN) and diamond are commonly preferred for

metal cutting. At elevated temperature hardness of cemented carbide decreases with

decrease in binder content. So, special powder preparation and processing techniques are

required to minimize the grain growth and provide adequate strength. Some improvements

in the toughness of ceramic tools have been achieved recently by alloying alumina with

TiC or with stabilized ZrO2 and by new processing techniques such as hot pressing and hot

isostatic pressing. A significant increase in fracture toughness accomplished with SIALON

based tool materials, though SIALON is not so hard enough. Diamond is one of the hardest

materials which can be used for hard machining, but it is very expensive. In contrast to

diamond, CBN (cubic boron nitride) is more preferable for machining of hardened

workpiece. CBN is chemically more stable than diamond when it is used for machining

ferrous alloys. It has good thermal stability; up to around 800 °C, this temperature can be

further increased by decreasing the impurity content with special processing techniques.

CBN tool is better than carbide and ceramic tools. It can perform 5 to 100 times better in

terms of longer tool life and / or higher removal rate than carbide or ceramic tools.

Proportionate harder cutting materials are required for machining of hardened workpiece.

Development of higher hardness materials like PCBN (polycrystalline cubic boron nitride)

has great importance to machining of hardened materials [4]. Ammonia and boron chloride

form a compound of Boron nitride (BN) as per following reaction:

BCL3 + NH3 → BN + 3HCL (1.1)

Boron nitride (BN) has hexagonal structure like graphite. Hexagonal structure of

hexagonal boron nitride can be transformed in to cubic structure under high temperature

Ch. 1 Introduction

4

and pressure and form a cubic boron nitride (CBN). This transformation is shown in Fig.

1.1.

FIGURE 1.1

Atoms of boron nitride changes from hexagonal to cubic structure [4]

Bonding strength of CBN is higher due to large amount of binders available in the cubic

structure of boron nitride. High wear resistance of CBN tool is observed, when machining

of hardened steel [6].

1.4 Cutting Conditions, Orientation of Three Dimensional Forces,

Surface Roughness and Wear of Cutting Tool Pertaining to Machining of

Hardened Materials

In process of turning, depth of cut, cutting feed and cutting speed are main cutting factors

affecting the performance of tool. Single point tool geometries like main cutting edge

angle, rake angle and tool nose radius have equal importance. Other input cutting

conditions like workpiece hardness and rigidity of machine tool need to be considered for

efficient machining. During turning, various forces are inducing on cutting tools. For

example, forces exerted in cutting direction, radial direction and feed direction are known

Cutting Conditions, Orientation of Three Dimensional Forces, Surface Roughness and

Wear of Cutting Tool Pertaining to Machining of Hardened Materials

5

as cutting (Fc), radial (Fr) and axial force (Fa) respectively. Three dimensional forces

relating to cutting tool insert are presented in Fig. 1.2.

FIGURE 1.2

Direction of cutting force, radial force and axial force on cutting tool insert

Cutting forces and stresses are continuously induced during the machining of metallic and

nonmetallic materials. Manufacturing industries are constantly focusing to increase

efficiency. There are many investigations pertaining the study of parameters and geometry

of tool on the forces of cutting for different metals [7]. Determination of appropriate

variables of cutting based on material removal rate and tool life has been carried out.

Moreover, morphology of chip, wear of tool, development of tool life equation, three

dimensional forces of cutting and their variations need to be analyzed [6].

Performance of finish hard turning is evaluated based on surface roughness of machined

component which is one of the vital output parameter of the process using different range

of cutting variables [8]. Also, preparation of cutting tool edge and nose radius of tool are

significantly important to obtain lower surface roughness [9].

Ch. 1 Introduction

6

A tool wear mechanism produced during hard turning has been investigated for better

machining and tool selection criteria. CBN is widely used tool as it has comparatively

higher wear resistance [4]. White layer formation and wear of tool are significantly

affected by cutting variables like depth of cut, feed and cutting speed [9]. Some analysis

was studies based on microstructure of steel and worn faces of tool flank and detected that

various particles of hard carbides present in material of workpiece produces grooves on

tool flank face by abrasion. Different wear rates were observed based on the degree of

hardness of carbides in the steels [6]. Wear of tool occurs due to combined or individual

effect of five wear mechanism like abrasion, adhesion, diffusion, fatigue and tribochemical

process. Abrasion and adhesion are referred as mechanical wear. Flank wear formation is

very critical and affects performance of machining more significantly. Flank wear

increases rapidly at initial stage of machining or at last stage of machining for three equal

stage of cutting length. Flank and crater wear are formed due to rubbing of workpiece and

sliding of chips on flank and rake faces of cutting tool [4, 10]. Shortly, individual as well

as simultaneous or coexistence effect of abrasion, adhesion, and diffusion may affect the

wear of CBN tool in hard turning [4].

Relative motion of workpiece and cutting tool is continuous and in great proportion which

is responsible for inducing high cutting tool forces, high temperature and friction at tool

workpiece interface in hard turning. This is the reason for wearing of tool faces which

damages the surface quality and reduces the precision in machined part. Wear is generated

by physicochemical mechanism and it is very complex to differentiate. Commonly, tool

wear occurs during severe cutting conditions in hard turning. It means variation of tool

geometry, tool forces and temperature produced in machining deteriorate surface quality of

workpiece material. Wear on all active faces of tool depends on the machining conditions

[4]. Figure 1.3 shows various wear produced on single point cutting tool during turning.

Cutting forces are induced during machining and affect the performance such as surface

roughness, wear of tool, temperature, vibration etc. Understanding of phenomena of

cutting force is an important in machining as it plays primary role to evaluate power

consumption, tool and material deflections. In hard turning, higher amount of cutting

forces are produced because of high hardness of material this affects the performance of

cutting tool [7].

Organization of Thesis

7

FIGURE 1.3

Different wear phenomenon on single point cutting tool [4]

However, geometries of tool like nose radius and inclination angle make the chip

formation process as a critical oblique cutting process. Some theory has been developed

which contains the geometry of tool along with cutting conditions to evaluate temperature

and forces [11].

AISI D2 steel which can be hardened up to 68 HRC is used in many engineering

applications. CBN possess certain advantages over other tool materials like diamond,

tungsten carbide, ceramic etc. Research related to turning of AISI D2 steel investigating

influence of tool geometries and different input cutting variables on surface roughness of

component, cutting forces and tool wear may be of great interest to machining industry.

This has provided motivation to take up this research with specific objectives as reported

in chapter – 2.

For clarity of presentation, content of the thesis is organized in different chapters as per the

detail given in following section.

1.5 Organization of Thesis

Thesis contains six chapters to address the objectives of research work. Outline of various

chapters is discussed below;

Ch. 1 Introduction

8

CHAPTER 1 describes back ground of hard turning, tool materials, workpiece materials,

cutting parameters, tool geometries, mechanism of cutting forces, science of tool wear and

surface roughness of machined part.

CHAPTER 2 emphasizes review of specific literatures attribute to analysis of surface

finish, cutting forces and wear of tool for turning of hardened material. It covers complex

mechanism of oblique cutting, impact of cutting variables and geometries of tool on

performance of machining. It also deals with the extensive modeling of three dimensional

forces of cutting, surface roughness and wear of tool studied by various authors. Finally,

overall findings of various literatures, objectives, scope of work and their significance are

presented.

CHAPTER 3 reports design of experiment and experimental work. It explains detail

experimental planning for hard turning experiments. It also mentions the details of

instruments used in experimentation and methods of measurement of output variables.

CHAPTER 4 shows experimental readings of three dimensional forces of cutting, surface

roughness of machined component and wear of tool. Also, influence of different cutting

variables on three dimensional forces of cutting, surface roughness and wear of tool are

analyzed in this chapter.

CHAPTER 5 demonstrates empirical modeling of surface roughness and forces in axial,

radial and cutting directions based on various cutting conditions to reveal correlation of

outcome with input variables in hard turning. It also shows the comparison between test

results and predicted outcome for validation of models of forces of cutting and surface

roughness.

CHAPTER 6 depicts summary of the important conclusions derived based on results of

presented research work and scope of future work.

References

9

References

[1] Pardeep Kumar SD, Aman Agarwal (2011) HARD TURNING VERSUS GRINDING, National

Conference on Advancements and Futuristic Trends in Mechanical and Materials Engineering.

[2] de Oliveira AJ, Diniz AE, Ursolino DJ (2009) Hard turning in continuous and interrupted cut with PCBN

and whisker-reinforced cutting tools, Journal of Materials Processing Technology, 209, 5262-5270.

[3] Bartarya G, Choudhury S (2012) State of the art in hard turning, International Journal of Machine Tools

and Manufacture, 53, 1-14.

[4] Huang Y, Chou YK, Liang SY (2007) CBN tool wear in hard turning: a survey on research progresses,

The International Journal of Advanced Manufacturing Technology, 35, 443-453.

[5] Davim JP (2011) Machining of hard materials, Springer Science & Business Media.

[6] Arsecularatne JA, Zhang LC, Montross C, Mathew P (2006) On machining of hardened AISI D2 steel

with PCBN tools, Journal of Materials Processing Technology, 171, 244-252.

[7] Kamely MA, Noordin MY (2011) The impact of cutting tool materials on cutting force, World Academy

of Science, Engineering and Technology, 51, 903-906.

[8] Bartarya G, Choudhury SK (2012) Effect of cutting parameters on cutting force and surface roughness

during finish hard turning AISI52100 grade steel, Procedia CIrP, 1, 651-656.

[9] Özel T, Karpat Y, Figueira L, Davim JP (2007) Modelling of surface finish and tool flank wear in turning

of AISI D2 steel with ceramic wiper inserts, Journal of materials processing technology, 189, 192-198.

[10] Thamizhmanii S, Hasan S (2009) Investigation of surface roughness and flank wear by CBN and PCBN

tools on hard Cr-Mo steel, Proceedings of the World Congress on Engineering, pp. 5.

[11] Arsecularatne JA, Fowle RF, Mathew P (1996) Nose radius oblique tool: cutting force and built-up edge

prediction, International Journal of Machine Tools and Manufacture, 36, 585-595.

Ch. 2 Literature Review

10

CHAPTER – 2

Literature Review

2.1 Introduction

Introduction to hard turning including its complexity, applications, cutting tools, cutting

conditions and its influence on three dimensional forces of cutting, surface finish and wear

of tool etc. is discussed in chapter 1. Out of the large amount of reported research available

related to hard turning, some important literatures based on the scope of this research work

are identified and discussed in this chapter.

Literatures addressing use of numerical, analytical and experimental methods for analysis

of hard turning of wide range of workpiece materials with different tool materials are

reviewed. It has been tried to report the literature exploring effect of cutting variables on

cutting forces, surface finish of machined part and mechanism of wear development during

turning of hardened materials. Range of cutting parameters used for hard turning with

different materials of workpiece and cutting tools are explored. Work reported depending

on contents of literatures are scrutinized and discussed in four different sub sections

namely; surface roughness of hardened materials, three dimensional forces of cutting in

hard turning, wear of tool, modeling of wear and cutting forces. After discussion on the

literature, overall findings based on literature reviewed, definition of the problem,

objective and scope of study and significance of study is reported.

2.2 Literature on Surface Roughness of Hardened Materials

Surface roughness of machined component is key factor for effectiveness of any machining

process. All factors considered in hard turning affect surface quality of workpiece in

different proportions. Most influencing parameters affecting surface roughness values are

feed, cutting speed and tool nose radius [1]. Moreover, built up edge formation [2] and

wear of tool phenomenon [3] affect the surface quality.

Literature on Surface Roughness of Hardened Materials

11

Various authors have investigated various aspects of hard turning and drew conclusions

regarding the surface roughness of machined part based on varying amount of cutting

conditions. Munoz-Escalona and Cassier [4] reported experimental work to study the

variation of smoothness of machined surface of workpiece for different nose radius of tool

and different cutting parameters. In addition, turning of various steel round bars (AISI

1020, 1045, 4140, D2) with different hardness was used to study the influence of

workpiece hardness on surface irregularity of machined components. Conclusion was

drawn by authors that surface roughness decreases with increase of nose radius of tool,

increase of cutting speed and reduction in feed.

Özel et al. [5] performed machining of hardened steel (AISI D2 steels, 60 HRC) with

ceramic tools of different nose radius. Full factorial design of experiments were applied to

perform experiments using three values of feed, cutting speed and cutting time with their

three levels and analyzed their influence on surface roughness. In the results, lower range

of surface roughness (around 0.18 – 0.20) µm was measured at low feed and highest

cutting speed. In addition, better tool life was obtained at lowest feed.

Many literatures pertaining to effectiveness of CBN tool used in machining of different

steels of high hardness along with different cutting parameters are studied. Özel et al. [6]

performed turning of hardened AISI H13 round bar (51.3, 54.7 HRC) using CBN tool.

Three different values of feed; 0.05, 0.1 and 0.2 mm/rev and two different values of cutting

speed; 100 and 200 m/min were used to analyze surface roughness. Also, they developed

functional relationship of surface roughness with feed, cutting speed and workpiece

hardness using regression analysis and artificial neural network. Authors obtained higher

surface roughness at high value of feed and hardness.

Bouacha et al. [7] performed hard turning using different cutting speed (125 - 246 m/min),

feed (0.08 - 0.16 mm/rev) and depth of cut (0.15 - 0.45 mm) with CBN tool. RSM

(response surface methodology) was used for analysis to study the influence of various

parameters to surface finish in machining of AISI 52100 steel having hardness of 64 HRC.

They observed that feed was most affecting parameter for variation of surface roughness

while depth of cut had very marginal effect on surface roughness. Conclusion also shows

that cutting speed has negative influence on surface roughness.


12

Aouici et al. [8] carried out turning of AISI H11 round bar of three different hardness (40,

45 and 50 HRC) with CBN tool using varying amount of depth of cut (0.15 - 0.45 mm),

cutting speed (120 - 240 m/min) and feed (0.08 - 0.16 mm/rev) to analyze their effect on

surface finish. Results of surface roughness were measured in the range of 0.34 - 0.83 µm.

Authors studied effect of two-factor interactions like hardness of component and cutting

speed, depth of cut and feed, cutting speed and depth of cut, hardness of component and

feed on finish. They concluded that interaction of feed and hardness of component

significantly affects surface roughness. They also concluded that high cutting speed and

lower feed showed lower surface roughness.

Bartarya and Choudhury [9] performed hard turning to study the influence of different

parameters on surface roughness. CBN tool was utilized for turning of AISI 52100 steel

(60±2 HRC). Regression equation of surface roughness was formulated based on full

factorial design of experiment using range of input parameters 167-261 m/min, 0.075–0.15

mm/rev and 0.1–0.2 mm for cutting speed, feed and depth of cut respectively. Average

value of surface roughness was achieved from 1.11 µm to 6.19 µm. Depth of cut, feed and

their interaction had significant contribution. On increasing of feed at low depth of cut,

surface roughness first decreases and then increases. Cutting speed had less influence on

surface roughness.

Besides variation of cutting parameters and tool geometries, some phenomenon like tool

wear greatly influence the performance of machining. Rech and Moisan [10]

experimentally investigated influence of cutting speed, feed and tool wear on surface

quality of 27MnCr5 steel while turning. They stated that feed and tool wear significantly

affect surface roughness in comparison to cutting speed. However, surface roughness

increases suddenly at high cutting speed between 200–250 m/min. It might be due to

sudden wearing of tool during turning.

2.3 Literature on Cutting Forces in Hard Turning

In material removing process, cutting forces are induced on tool in radial, axial and cutting

directions. In hard turning, it is important to give proper attention on mechanism of cutting

forces as it is essential for taking decision for selection of tool geometry and its material.

Investigation of tool performance is reported by different researchers [11-13] and observed

that it depends on many variables like depth of cut, feed, cutting speed, wear of tool and

Literature on Cutting Forces in Hard Turning

13

cutting forces. Various researchers reported the effect of cutting conditions, material

hardness and geometries of tool on three dimensional cutting forces.

Bartarya and Choudhury [9] investigated variation of three dimensional forces in cutting

based on depth of cut, feed and cutting speed in turning of hardened steel of AISI 52100

(60±2 HRC) using CBN tool. Experiments were performed using full factorial design of

experiment for three different values of depth of cut (0.1, 0.15 and 0.2 mm), feed (0.075,

0.113 and 0.15 mm/rev) and cutting speed (167, 204 and 261 m/min). Combined effect of

machining parameters on cutting forces was also investigated. Forces in cutting, radial and

axial directions were more sensitive with depth of cut than feed. Cutting speed had least

contribution to radial and axial force. Authors also reported development of cutting forces

model based on regression analysis.

Few researchers also investigated effect of workpiece hardness on cutting forces along

with effect of main cutting parameters. Aouici et al. [8] reported hard turning mechanism

to show influence of different variables on three dimensional forces in cutting with the

variable depth of cut 0.15-0.45 mm, feed 0.08-0.16 mm/rev, cutting speed 120-240 m/min

and hardness of materials 40, 45 and 50 HRC. Experiments were carried out on AISI H11

steel using CBN tool. Results of tangential, axial force and thrust force were measured in

the range of 59.76–302.28 N, 41.13–166.95 N and 99.71–369.35 N respectively. Results

showed that depth of cut influenced cutting force components significantly followed by

workpiece hardness. Contribution of depth of cut towards cutting and axial force was

found to be 31.50 % and 56.77 % respectively. While, cutting speed had lower

contribution (0.14 %) on forces. Authors also concluded that lower axial force was

obtained at lower feed and moderate amount of cutting speed. Interaction effect of depth of

cut and hardness of workpiece material influenced the axial force. It was observed that

lower axial force was obtained at lower depth of cut and lower hardness of workpiece

material.

Cutting forces also varied with radius provided at cutting edge of tool and had significant

impact on three components of cutting forces in turning of hard metal. Liu et al. [14] performed turning of hardened JIS-SUJ2 steel and investigated the influence of nose radius

of CBN tool on cutting forces under dry condition. Experiment was performed at depth of

cut of 0.1 and 0.2 mm, constant feed of 0.1 mm/rev and constant cutting speed of 120


14

m/min. Authors concluded that progressive increase of nose radius increases the thrust

force.

Arsecularatne et al. [15] performed turning of hardened AISI D2 steel (62 HRC hardness)

with PCBN cutting tool. Various values of three dimensional forces induced in cutting

were reported during machining which was carried out at different values of cutting speed

(70–120 m/min), feed (0.08–0.20 mm/rev) and 0.5 mm constant depth of cut. From

graphical representation of cutting force, radial force and axial force components, they

found that axial forces was the smallest force, cutting force was the largest force and radial

force lied between axial and cutting force.

Tönshoff et al. [16] studied relationship between cutting forces and material hardness.

Turning of AISI 4030 round bar was performed using constant depth of cut, feed and

cutting speed of 0.15 mm, 0.9 mm/rev and 90 m/min respectively. They analyzed forces

and concluded that hardness of material affect the cutting forces. Cutting forces for cutting

of soft material were high and observed to be decreasing with increase in workpiece

hardness. While cutting forces were observed to be increasing with increase the hardness

of material above 50 HRC. This increase amount of cutting forces raised temperature at

work area due to energy consumption resulted in increase of thermal load in hard turning. Authors selected low feed and small depth of cut to reduce mechanical and thermal loads

on tool. Moreover, increases of tool wear due to increase in cutting time affected cutting

force component greatly.

2.4 Literature on Tool Wear

Extensive research work is reported addressing prediction of wear of tool in turning of

hardened materials as it is the measure of tool failure.

Various authors described different reasons for development of tool wears in metal cutting

operations. Waydande et al. [17] studied phenomenon of tool wear produced during hard

turning. They concluded that constant heat is generated due to continuous shear and

friction during turning and as a results high temperature is induced at tool and chip

interface. They reported different types of wears observed at tool faces due to combine

effect of adhesion, abrasion and diffusion. Amongst that; wear of crater, flank and notch

were commonly observed in turning of hardened material. They concluded that friction

Literature on Tool Wear

15

produced between flank face and workpiece was responsible for flank wear. Wear land of

flank face was observed along the major and minor cutting edges of tool due to abrasion

between cutting tool and workpiece component. Crater wear was observed on rake surface

as a result of adhesion and diffusion of chip particles and small elements of rake face.

Chemical or metallurgical wear was induced due to mechanical friction along the major

cutting edge. Authors also described notch wear due to combination of wears of rake and

flank surface besides to intersection point between primary cutting edge and workpiece. Previous passes during cutting and mechanical thrust which was induced due to wear

caused surface hardening of workpiece.

Anthony et al. [18] reported wear pattern which was created due to adhesion with

continuous machining. Adhesion was produced due to high temperature and pressure

created at shear zone and it joins rake face and chip temporarily. As a result, lose particles

removes from soft surface. Adhesion was commonly found in aluminium alloys, but it was

not usual in hard turning. They also reported softening of materials at high temperature,

notching and diffusion and their resultant effect on wear of tool. However, it was difficult

to obtained tool life equation based on cutting variables like cutting parameters and

geometries of tool as well as properties of tool and workpiece materials. They reported

some critical problems occurred due to shortage of relevant details, high temperature and

high rate of strain. Also, various factors influenced tool life like material of workpiece and

tool, machine tool, geometries of tool and cutting parameters.

Arsecularatne et al. [19] concentrated on various literatures pertaining to flank wear and

tool life while machining with WC (tungsten carbide), PCBN (poly-crystalline cubic boron

nitride) and PCD (poly-crystalline diamond) tool materials. Authors described dominant

wear pattern of PCBN and tungsten carbide tool. Wear mechanism due to abrasion,

adhesion, micro-cracking and fatigue was used to explain wear of PCD tool. But,

unfortunately wear of PCD tool was not understood due to non-availability of experimental

results. Authors concluded that chemical wear found to be main wear phenomenon for

PCBN tool. They also reported that diffusion was the dominant wear mechanism for WC

tool and steel combination. Moreover, progressive flank wear was observed on tool flank

face and it was useful to define tool life. Flank wear progression caused increase in the

wear land. Also, surface quality and dimensional accuracy of machined part get affected

after certain level of flank wear.


16

Liu et al. [14] reported the influence of tool nose radius on flank wear of CBN tool in hard

turning of JIS-SUJ2 bearing steel under dry condition. Experiment was performed using

depth of cut of 0.1 and 0.2 mm. Cutting speed and feed kept constant and were 120 m/min

and 0.1 mm/rev respectively. Authors concluded that friction produced at tool–workpiece

interface significantly contributed to flank wear. Friction developed between tool and

workpiece increases with increase of tool flank wear and resulted in increase of cutting and

thrust force on cutting tool. Also, residual tensile stresses at machined workpiece increased

remarkably with increase of tool wear.

Remadna and Regal [20] applied different methods to perform experimental work. In first

method experiment was performed with constant cutting speed, while in the second

method, variable cutting speed from 100-300 m/min was introduced in turning.

Measurements of tool wear at regular interval were recorded to scrutinize the phenomenon

of wear along tool faces. They concluded that shape of wear developed in cutting was

attributed to geometry of tool, cutting parameters and workpiece material. However, wear

of CBN tool did not affect the quality of surface directly. Wear progression affected

cutting force which altered the functioning of system because of inter-relationship between

workpiece and cutting tool.

Ozel et al. [5] used different combinations of feed (0.05, 0.10 and 0.15 mm/rev) and

cutting speed (80, 115 and 150 m/min) to perform turning of hardened AISI D2 steels

having hardness of 60 HRC. Experiment was carried out using 0.2 mm depth of cut and

tool having ceramic material to obtain model of tool life. Predictive model of tool wear

was developed using neural network and multiple linear regression method. After

machining for around 15 minutes at high cutting speed, tool flank wear was observed 0.15

mm and it was considered as tool life criterion. They concluded that lowest cutting speed

and feed combination results into best life of tool.

Turning of AISI D2 steel with 62 HRC hardness was performed by Arsecularatne et al.

[15] with PCBN tools at different range of cutting speed (70–120 m/min) and feed (0.08-

0.20 mm/rev) combinations. Flank wear was used as criteria for deciding tool life. Lowest

speed (70 m/min) results into highest tool life among the selected tool and workpiece

combination. Most appropriate feeds for roughing and finishing operation were observed

0.20 mm/rev and 0.14 mm/rev respectively. Authors used Taylor tool life equation which

was used to define correlation of cutting parameters with tool life.

Literature on Tool Wear

17

Zhou et al. [21] reported the influence of chamfer angle on wear of flank face of PCBN

tools in turning of hardened 100Cr6 steel having hardness of 60-62 HRC. Finish hard

turning was performed using depth of cut, feed and cutting speed as 0.5 mm, 0.05 mm/rev

and 160 m/min respectively. Various tools with varying amount of chamfer angles between

00 and 30

0 were selected along with other geometries like constant cutting edge radius of

0.01 mm and 0.1mm chamfer width. It could be observed that tool life increases and

reached maximum when chamfer angle increases from 00 to 15

0.

Kishawy and Elbestawi [22] described influenced of flank wear on surface roughness of

machined component. Workpiece material AISI D2 having 62 HRC hardness was used to

perform turning to analyze the surface roughness of machined component using different

range of cutting speed, feed and depth of cut of 140-500 m/min, 0.05-0.2 mm/rev and 0.2-

0.6 mm respectively. PCBN tools having honed nose radius of 0.0125 mm and sharp

chamfer of 200×0.1 mm were used. Authors concluded that tool wear rate was increased

with increasing the value of cutting speed above 350 m/min. So, it deteriorated the surface

finish of machined component and this caused the material side flow during machining.

Moreover, feed and cutting speed combination was found to be main cause of micro cracks

and cavities. Due to phase transformation during machining, machined surface found

thermally affected and white layer was formed especially with chamfered or worn tools.

Tool life of different tools depends on wear rate of different materials. Sahin [23]

compared the tool life of cubic boron nitride (CBN) cutting tools and ceramics tools while

turning of hardened bearing steels. Performance of CBN tool was reasonably good than

ceramic tool. Also, investigation of effect of feed, cutting speed and hardness of cutting

tools on the life of tool was carried out based on the L9 orthogonal array in Taguchi

method. It could be seen from the results that the cutting speed had major contribution

which influenced wear of tool than hardness of workpiece and feed. Optimum cutting

conditions were evaluated based on tool life using signal to noise ratio. For effective

prediction, regression model was applied to develop exponential model. ANOVA

performed at 90% confidence level revealed different contribution of variables which

affected tool life. The contribution of feed, cutting speed and hardness of material was

observed to be 25.22 %, 41.63 % and 32.68 % respectively.

Various authors have performed turning of hardened materials using different cutting

parameters, tool geometries and different hardness of workpiece. It is important for


18

machinist to work in appropriate range of various cutting conditions to improve

performance of turning. Here, efforts have been made to accumulate such technical data

specifically for hard turning and reported in Table 2.1.

TABLE 2.1

Different cutting conditions used in various literatures during hard turning

Table 2.1 shows different hardened materials used in turning process which was performed

with the various range of depth of cut, feed, cutting speed, nose radius of tool and tool

materials.

Here, it is necessary to identify contribution of all input factors on the performance of

turning as they are functionally related with each other. In oblique cutting system it is very

difficult to develop relationship which shows interaction effect of various parameters on

output. As per above reported literatures, force and wear draws attention towards the

performance of hard turning as it influenced surface roughness, design of tool and power

consumption. Various authors have developed models based on empirical and analytical

methods for cutting forces and tool wear which are described in successive section.

Sr.

No

Workpiece material

(hardness) r (mm) Tool material v (m/min) f (mm/rev)

d

(mm)

1 JIS SUJ2 (60 HRC) [14] 0.4, 0.8,

1.2 CBN 120 0.1

0.1,

0.2

2 AISI 52100 (60-62 HRC)

[24]

0.8, 1.6,

2.4

Alumina, titanium-

carbide

composite

120 – 180 0.05 – 0.6 0.2

3 H13 steel (56 HRC) [25] 0.4 CBN 144.26,

288.52 0.172 0.2

4 AISI D2 (60 HRC) [26] 0.8 CBN, Ceramic 100, 140,

200 0.06 0.4

5 AISI D2 (60±1 HRC) [5] 0.8 Ceramic 80, 115,

150

0.05, 0.10,

0.15 0.2

6 AISI D2 (62HRC) [15] 0.8 CBN 70, 95, 120 0.08, 0.14,

0.20 0.5

7 AISI D2 (58 HRC) [27] 0.8 Mixed alumina 80–150,

220

0.05–0.10

and 0.15 0.2

8 AISI D2 (60 HRC) [28] 0.8 Ceramic tool 80, 150,

220

0.05, 0.10,

0.15 0.2

9 AISI D2 (54HRC) [29] 0.8 CBN 120, 180,

230 0.08, 0.12 0.2

Literature on Development of Models of Crater Wear, Flank Wear and Cutting Forces During Turning of

Hardened Material

19

2.5 Literature on Development of Models of Crater Wear, Flank Wear

and Cutting Forces During Turning of Hardened Materials

Various models were developed and utilized by many authors to optimize performance of

hard turning. In this section, different models have been reviewed for turning of hardened

materials using CBN (cubic boron nitride) tool. Here, efforts are made to describe

appropriate empirical and analytical models. Different models pertaining to crater and

flank wear model, model of oblique cutting force, Usui‘s wear model, force model of

extended Lee and Shaffer, morphology of chip and flank wear progression are reported

here to recognize the relationship of different parameters and geometries of tool with

forces and wear developed in machining. Different methods are reported to scrutinize the

influence of cutting variables on forces and wear of tool developed during experiments.

Various modeling of cutting forces and tool wear are reported here. So, suitable model can

be applied as per necessity of industries of manufacturing of hard components.

2.5.1 Literature on Modeling of Tool Wear

Many authors reported literatures on modeling of tool wear and its influence with cutting

forces and surface roughness. Özel et al. [5] stated that tool crater wear and flank wear

directs the tool life and were main factors contributing to dimensional variation and

reduction of surface quality of materials. Additionally, reported research shows that

inaccuracy and instability of tool motion during machining was produced as a consequence

of wear of tool and hence cutting forces [5, 30, 31].

Different approaches for development of cutting force model in association with chip

morphology had been applied based on different numerical, empirical and analytical

method. Chang [32] analyzed the forces in cutting, radial and axial directions considering

effect of tool wear. Many authors [8, 33, 34, 35] investigated the effect of different

material hardness (50-64 HRC) on tool wear under moderate feed, cutting speed and lower

depth of cut for hard turning. Huang and Liang [36] developed model of tool wear using

analytical approach and finite element method (FEM).

Huang et al. [37] reported extensive survey on wear of CBN tool in turning of hardened

component. They described causes of wear and its influence on performance of hard


20

turning. Commonly, interaction effect of diffusion, adhesion and abrasion was found to be

major factors affecting wear of CBN tool during turning of hardened materials. However,

authors concluded that discrete wear phenomenon was dependent on type of material of

workpiece and tool, tool-workpiece orientation, cutting parameters, geometry of tool,

properties of CBN tool such as grain size, binder phase and content of CBN. Apart from

main wear mechanism like flank, crater and nose wear; some wear was observed due to

notching and micro-chipping on CBN tool during hard turning. But authors drew final

conclusion that only flank and crater wear required greater attention for research as it has

greater influence on metal cutting performance. Bouchelaghem et al. [33] developed

mathematical models to evaluate the relationship between cutting speed and life of CBN

tool. Authors concluded that tool wear was key variable for performance evaluation as it

affected surface quality of machined component. Also they stated that consistency of

process were reliant on tool wear phenomenon. Also, surface finish and precision of the

machined work piece reduced due to tool wear. Authors stated that mechanism of wear is

very critical process as it follows physicochemical mechanism developing at contact faces

of component, chip and cutting tool. Due to destruction of active tool surface, fresh surface

would come in contact with work piece resulted in changed tool geometries and reduction

of surface quality of machined part.

So, it is essential to understand the phenomenon of tool flank and crater wear which are

typically caused due to abrasion, adhesion, and diffusion. Here, various models pertaining

to flank and crater wear progressions are depicted along with their relative importance.

LITERATURE ON MODEL DEVELOPMENT OF FLANK WEAR OF TOOL:

Systematic approach has been applied to develop analytical modeling based on different

wear rate for hard turning. Some literatures describe various wears which are developed on

CBN tool more specifically in hard turning that have great contribution for analysis and

evaluation of flank wear.

Huang and Liang [38] developed wear model using chamfered tool geometry on tool nose

radius of CBN tool while turning of hardened material. Very little influence to crater wear

was assumed with variation of rake angle of tool. Cutting speed (Vc) abrasive particles

hardness (Pa) normal shear stress (σ) and hardness of tool (Pt) greatly affected the flank

wear during metal cutting operation. In addition, abrasion and adhesion had significant

contribution on tool wear during machining of hard material. Moreover, tool wear rate was


Hardened Material

21

varied with geometrical parameters like nose radius (r) of tool and relief angle of tool (γ).

Flank wear loss during time span (dVb/dt) was formulated as per (2.1).

/( 273)

1

d (cot tan )

d [ tan ] Q T

n

aabrasion c bb n

tb b

KaTadhesion c diff c b

PK K V VV r

Pt V r V

K e V K V V e

(2.1)

Kdiff, KQ, Kadhesion, Kabrasion and a are the coefficients which can be calibrated experimentally

for different tool and workpiece. Wear model as shown in (2.1) can be compared with

experimental results of tool wear obtained with in specified range of cutting conditions

recommended by manufacturer of cutting tool for validation. Authors compared the

proposed model with experimental results which found very close with each other.

LITERATURE ON MODELING OF CRATER WEAR: Cutting parameters and

geometrical dimensions of tool can be evaluated from crater wear modeling for finishing

operation performed by turning of hardened steel. Tool failure is caused due to micro

chipping, breaking of tool tip and progressive flank wear under critical cutting parameters

which wears rake face (crater wear) and reduce the strength of cutting edge.

Huang and Dawson [39] developed model pertaining to crater wear progression. Various

factors like tool geometry, cutting parameters and tool and workpiece materials

significantly affected wear of rake face. Huang and Liang [40] reported model of crater

wear based on assumptions like ―All material loss causes due to crater wear as a results of

diffusion, adhesion and abrasion.‖ Depth of wear progression on rake face was formulated

as shown in (2.2) as;

273

1

d

/ ( ) d

Q

T

n

aabrasion chip

nT

tT

KaT

adhesion c dif c b

PK K V h

K P D Kt

K e V h K f V V e

(2.2)

Another approach for modeling crater wear of CBN tool was formulated by Huang and

Dawson [39] and compared with wide range of cutting conditions for validation of

modeling. Resultant effect of diffusion, adhesion and abrasion influenced tool wear

phenomenon in turning of hardened workpiece.


22

FIGURE 2.1

Geometrical nomenclature of crater wear of CBN tool used in turning of hard materials [39]

Based on Fig. 2.1, various defined factors like crater wear depth (KT), length of contact (h)

and radius R and their relationship can be seen in (2.3).

2

22

2

hR R KT

(2.3)

Cutting conditions were optimized based on the proposed wear depth model for

determination of tool life and tool design. So, wear resistance can be increased specifically

for turning of hard materials.

But, Huang et al. [37] came up with conclusion that crater wear required to be considered

only in aggressive cutting parameters. While flank wear was most significant criterion for

tool rejection.

LITERATURE ON MODELING OF WEAR BY GENERALIZE APPROACH:

Thamizhmanii and Hasan [41] reported effect of friction which was produced between tool

and workpiece. Friction played crucial role in wear that include material transfer and

changes of physical properties of material during metal cutting. Also, authors developed

relationship of total wear which was produced due to change in mechanical and chemical

properties with relative motion of cutting tool and workpiece as (2.4).

Wear total = W mech + W chem. [41] (2.4)

Research reported by various researchers was studied to analyze the interaction effect of

absolute temperature (T), relative cutting speed (Vs) and normal stress (σn) corresponding

to tool wear [42-44]. Usui‘s tool wear approach was applied to evaluate tool wear rate as

reported in (2.5).


Hardened Material

23

n s

BdW expA V

dt T

(2.5)

Where, A and B are constants

2.5.2 Literature on Analytical Modeling of Cutting Forces

Better understanding of metal cutting process required proper attention on cutting forces as

geometrical and cutting parameters are related closely with each other. Tool flank and

crater wear progression significantly affect tool geometry and hence machined surface of

the component. Change in tool geometry also affects heat generation during hard turning.

Here effort is made to report specific reviews related to model development of three

dimensional forces induced in metal cutting which shows correlation of all possible cutting

variables.

Orthogonal cutting was used to develop various models. Also, force model based on

oblique cutting approach, chip morphology, flank wear progression and extended Lee and

Shafer‘s theory was reported using different cutting parameters. Moreover, changes in

developed analytical force models and their analysis based on tool wear were described by

many authors.

Strenkowski et al. [45] developed analytical model considering friction which induces on

the tool face based on undeformed chip thickness t1. Cutting velocity and chip flow

velocity were used to define effective rake angle αe. Also, normal force and thrust force

were evaluated based on normal force and friction force. Equation (2.6) shows formulation

of friction force F.

1 sin cos cos sin cos cos

s e

e e e n

btF

i

(2.6)

Authors also considered shear plane to evaluate principal tool force. Equilibrium of energy

was applied to evaluate the principal tool force FH as shown in (2.7) considering area of

shear plane (A).

cos

cos( ) cos cos cos

1s eH

e e e e n

btF A

i

(2.7)


24

On the determination of normal rake angle, effective rake angle, friction force and

principal force, it was easy to determine the normal force N as per (2.8).

cos cos sin n e HN i F F

(2.8)

Thrust (Ft) and cutting (Fc) force were evaluated as per (2.9) and (2.10), respectively.

cos sin sin cos cos sin sin t n c c nF N i F i F i

(2.9)

sin cos cos c n c nF N F

(2.10)

Orthogonal cutting mechanism and Usui‘s approach were applied for determination of

different factors like shear angle ( ), shear stress (τs) and friction angle (β) presented in

thrust and cutting force modeling. Inclination angle (i), rake angle (αn), chip thickness (t1)

and width (b) are known value for any machining process using different cutting

conditions. Angle of chip flow (ɳc) can be evaluated based on principle minimum energy

approach. Model was compared with the results of experiments performed using tools

having different nose radius for validation. Closeness of predicted results was found with

measured three-dimensional cutting forces.

Moreover, different theories and experimental techniques had been reported based on

friction induced between tool and chip during metal cutting. Many researches were carried

out to focus on some complications produced during hard machining to identify

phenomenon of friction and material selection of tool. Many authors recommended slip

line theory for modeling of chip development during metal cutting. In slip-line model, the

material flow at specific shear zone was considered rigid plastic state. Fang [46] applied

extended Lee and Shaffer‘s model based on slip-line theory for effective prediction

attributed to Fig. 2.2.

Where, α is tool rake angle, t1 is undeformed chip thickness, Vch is velocity of chip, ϕ is

shear plane angle and k is referred as flow stress of material. For more specifically, some

dimensionless factors Ft/kt1w shown in (2.11) and Fc/kt1w shown in (2.12) in terms of

thrust Ft and cutting force Fc force were developed as:

1

sin sin4

1 2 tan 1 [1 2 2 2 sin(2 )] cos cos

tFef ef

kt w

(2.11)


Hardened Material

25

FIGURE 2.2

Material removal concept based on extended Lee and Shaffer’s model using negative rake angle tool

[46]

1

sin sin( )4

1 2 tan cos(2 ) cos cos

cFef X

kt w

(2.12)

In analytical work, error was formulated by author using the equation of ΔD for effective

prediction based on ratio of chip thickness t2/t1 and forces Fc/Ft as shown in (2.13). Terms

‗expe‘ and ‗pred‘ described in (2.13) are known as experimental and predicted results

respectively. Lower value of ΔD was selected for appropriate cutting conditions.

22

2 2

1 1

c c

t tpred expe pred expe

t tF FD

F F t t

(2.13)

Extensive orthogonal cutting tests was performed by author using wide span of cutting

speeds in the range from 120 m/min to 1120 m/min and −60° negative rake angles of tool

and validated the model presented in (2.11) and (2.12). Error variation between

experimental and predicted readings observed less than 1%.

Comprehensive analysis was carried out to complete understanding of three dimensional

cutting forces produced during hard turning. Many researchers studied the mechanism of

force development based on simultaneous effect of chip formation and wear of tool. Huang

and Liang [47] used planar mechanistic force model which was extended to develop three

dimensional force model with the analysis of chip formation. Forces in cutting (P1), axial

(P2), and radial (P3) directions based on influence of tool specifications and obliquity were

modeled as per (2.14) and (2.15).


26

1

2

3

* *

* – *

c

t s r s

t s r s

P F

P Fcos C F sin C

P F sin C F cos C

(2.14)

cos sin

cos sin

(sin cos sin tan ) cos tan

sin sin tan cos

c n f

t f n

c t

r

F K Acutting K Acuttingn n

F K Acutting K Acuttingn n

F i i Fn c n cFi in c

(2.15)

Authors used various equivalents of angles presented by Arsecularatne et al. [48] to

convert two dimensional force model in to three dimensional cutting forces. Angles

reported in (2.14) and (2.15) were equivalent side cutting edge angle (Cs*), equivalent

inclination angle (i*) and equivalent normal rake angle (αn*) which described mechanism

of three dimensional cutting forces. Experimental results of cutting forces were used to

evaluate the cutting pressure coefficients Kn and Kf. Besides cutting forces developed based

on formation of chip, Huang and Liang [47] considered the effect of flank wear of tool in

cutting forces. Force model related to progressive wear of flank face was converted into a

three-dimensional analysis using modified Waldorf‘s orthogonal force model. Force model

based on progressive wear of flank face described relationship between cutting forces and

cutting variables like small dept of cut, low feed and relatively large nose radius of tool.

Equations (2.16), (2.17) and (2.18) describe three dimensional forces in cutting, axial and

radial directions respectively. Arc ABD shows portion of nose of tool and separated in to

various size of chords dl along the flank face of tool as displayed in the Fig. 2.3. Also,

Waldorf‘s force model of worn tool was used to determine the values of shear stresses τw

and normal stress σw.

Lastly, forces developed based on chip morphology and progressive flank wear of tool

were utilized to evaluate total forces in the tangential, feed and radial directions. Huang

and Liang [47] validated analytical models of cutting forces using experimental results

obtained in turning of hardened AISI 52100 steel (62 HRC). Predicted value of total

cutting forces fits effectively with experimental readings.


Hardened Material

27

FIGURE 2.3

Orientation of cutting forces based on progressive wear of flank face of tool in hard turning [47]

2

1 0

/2 2

1 0 /2 0

1 0

( )d d (2.16)

cos sin2

( )cos d d ( )sin d d (2.17)2

sin cos2

VB

wcutting cw w

ABD

waxial tw tw

AB BD

VB VB

w w

wradial tw tw

AB BD

VB

F F r z z

F F F

r z z r z z

F F F

r

/2 2

/2 0

( )sin d d ( )cos d d (2.18)2

VB

w wz z r z z

Sadik [30] reported the impact of wear on forces induced in machining. Consideration of

cutting forces was very indispensable for selection of suitable tool specifications and

material of tool. Huang and Liang [47] analyzed that the consideration of cutting forces

was essential for tool rejection criteria which could be seen in the thermal modeling

developed based on various conditions in hard turning. Also, wear phenomenon, negative

1 1Where 1 AOO' cos (f/ (2r)) and 2 OO' sin (( ) / )D r d r


28

rake angle of tool and different cutting parameters was utilized to develop oblique cutting

system.

Overall, input factors influencing output variables were reported and analyzed specifically

for systematic implementation and detailed knowledge of cutting forces and wears of tool

in the turning of hardened components.

2.6 Findings of Literature Review

Overall findings based on the extensive literature review are reported as per following

remarks;

Hard turning is widely used for manufacturing of parts of hardened ferrous

materials having applications in high pressure dies, tools, automotive parts like

cams, shafts etc.

Generally, hard turning was performed using ceramics and CBN tools as described

in various literatures. Performance of CBN tool observed to be better in comparison

to ceramics tool. So, preference should be given to CBN tool for hard turning.

From analysis of surface roughness, effect of machining variables like depth of cut,

feed and cutting speed on surface roughness was described in reported literatures.

Lower surface roughness was achieved using lower depth of cut, low feed and high

cutting speed. Also, nose radius of tool showed greater influence on surface

roughness of machined part.

From analysis of cutting forces, it could be observed that feed had significant

contribution for the variation of cutting forces in the comparison of depth of cut

and cutting speed.

Various researchers carried out experimentation as per the different range of cutting

conditions. Common range of parameters include 80-180 m/min cutting speed,

0.05–0.2 mm/rev cutting feed, 0.2–0.5 mm depth of cut and 0.4–1.2 mm tool nose

radius.

Different models of cutting forces and wear were evaluated based on cutting

variables. It could be observed from analytical modeling that cutting parameters

and tool geometries were functionally related to cutting forces and surface

roughness.

Objectives and Scope of Study

29

Moreover, progressive flank wear required to take into consideration during

modeling of cutting forces.

2.7 Definition of the Problem

Since decades of research in the turning process, different theories and mechanisms are

continuously modified and developed for enhancing accuracy of prediction of three

dimensional forces in metal cutting and surface quality based on different cutting variables.

This research depicts mechanism of oblique cutting of hardened materials which is

complex to analyze. Different geometrical and cutting parameters affect the performance

of hard turning. Individual or simultaneous effect of depth of cut, feed, cutting speed and

tool nose radius affects the irregularity of machined surface, wear of tool and three

dimensional cutting forces. Optimum cutting conditions need to be evaluated based on

lower surface roughness. Evaluation of three dimensional cutting forces in cutting, feed

and radial directions is essential for selection of cutting tool. Progressive tool flank wear is

also having great importance in terms of tool life which affects cutting forces. It is very

difficult to develop relationship of cutting forces along with progressive flank wear based

on different cutting conditions and tool geometry. Here, model of three dimensional

cutting forces is developed by simplification of complex oblique cutting of hardened

material. Moreover, cutting speed, feed and nose radius of different CBN tools (depth of

cut constant 0.2 mm) significantly contributing to surface roughness of hardened AISI D2

steel. So, critical part of model generation of surface roughness is to inculcate the

simultaneous effect of feed, cutting speed and tool nose radius for effective prediction.

2.8 Objectives and Scope of Study

OBJECTIVES:

To perform experimental investigation for optimizing the machining parameters and

tool nose radius for minimizing tool forces and surface roughness in hard turning of

AISI D2 steel using CBN tool.

To develop the model for prediction of three dimension forces as a function of

machining parameters, nose radius and tool angles.


30

To enhance accuracy of force model by including the effect of progressive flank wear

of CBN tool measured at optimum cutting conditions during hard turning and validate

that model with experimental results.

To develop model of surface roughness of machined part which includes simultaneous

effect of all possible factors during hard turning.

SCOPE OF WORK:

There is a major difference in tooling and mechanism used in turning of materials in

hardened and normal condition. Hard turning is performed for manufacturing of

specific high pressure dies, tools, automotive and hydraulic parts for high accuracy,

finishing and more productivity. Various cutting conditions along with tool geometries

affect surface finish of machined part. From this work, manufacturers of various

components which are made from AISI D2 steel can get complete details of effect of

variation of cutting conditions and tool geometries on surface roughness. So, optimum

cutting conditions can be obtained based on their requirement of surface roughness of

AISI D2 steel.

This work is also helpful to design CBN tool considering effect of tool geometries like

tool nose radius and tool angles on cutting, radial and axial forces which is essential to

provide required strength to cutting tool for hard turning.

Influence of progressive flank wear of tool on cutting forces is analyzed and model is

developed for prediction of cutting variables. So, this can be useful for prediction of

wear of tool flank face and their influence on cutting forces during hard turning.

Simultaneous effect of all possible input parameters like feed, cutting speed and tool

nose radius are included in the modeling of surface roughness. Also it can be extended

by using other variables like depth of cut, hardness of materials etc.

2.9 Significance of Study

Various hardened materials used in manufacturing of different dies, tools, bearings etc.

draws specific importance in manufacturing industries. Now, machining of hardened

materials is possible due to advancement in the materials of tool like cubic boron nitride

(CBN). Trend of variation of surface roughness of hardened steel depends on the input

cutting conditions. Dependency of flank wear of tool on cutting condition and nose radius

Research Methodology

31

can be analyzed from this reported work. It is difficult to understand the phenomenon of

three dimensional cutting forces developed on the cutting tool during hard turning. Various

modeling of cutting tool forces are reviewed for different input variables. Conceptual and

simplified model of cutting tool force is described which is very effective for prediction of

three dimensional forces. Further, functional relationship can be observed between the

cutting, feed and radial force with cutting conditions and tool nose radius. So, industry can

utilize this model to check the effect of variation of cutting conditions and tool geometries

on the performance in terms of surface roughness of machined part and cutting tool forces.

Commonly, wear of flank face increases with cutting time in any metal cutting process. It

influences smoothness of machined part and cutting forces. So, it is required to consider

the flank wear progression for effective prediction of output based on input variables. This

work describes the modeling of flank wear progression which can be used for investigating

its effect on cutting tool performance.

2.10 Research Methodology

Systematic approach has been utilized to reach the final conclusions for this research. It is

required to formulate design of experiments before starting any experimental work. Also,

selection of cutting parameters is based on literature review and availability of set up for

experiments. In this work, cutting forces and surface roughness were measured and

systematically utilized to develop models of surface roughness and cutting forces.

Accuracy of prediction of developed models were verified by comparing it with other sets

of experimental readings. Finally critical findings were highlighted in conclusions.


32

FIGURE 2.4

Flow chart of applied research methodology

References

33

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Ch. 3 Design of Experiment and Experimental Work

36

CHAPTER – 3

Design of Experiment and Experimental Work

3.1 Overview

This chapter includes discussion on design of experiment, specification of workpiece,

specification of cutting tool, specification of machine tool, description of various

equipment and measuring instruments used and in-depth discussion on experimental

methodology.

3.2 Design of Experiment

Decision on input and output variables before performing experiments on turning operation

is crucial. Machining input variables like depth of cut, feed and cutting speed are common

input variables for any metal cutting process. Based on the finding from extensive

literature review, different input cutting conditions are selected for certain specific reason.

Depth of cut is kept constant for experiments on hard turning. As presented research is

related to finish hard turning, depth of cut is selected as 0.2 mm based on literature review. CBN tool is selected for turning. Whereas, feed, cutting speed and tool nose radius are

used as a variable input factors for turning experiments. For detail experimental

investigations, full factorial design of experiment which include experimental run for all

possible combinations of the input parameters is selected. Values of input variables such as

feed, cutting speed and nose radius of CBN tools are selected based on findings of

literature review, targeted output parameters, specifications of machine tools selected for

turning experiments and availability of standard CBN tool. Table 3.1 shows values of

various input parameters selected for turning experiments. Three levels are selected for

each input variables in order to predict the nonlinear relationship between input and output

variables if any.

With the reference of overall conclusion of literatures in order to fulfil the objectives and

aim of the presented work, output parameters selected for this research includes;

Design of Experiment

37

1) Surface roughness of machined part

2) Tool flank wear

3) Three dimensional tool forces

TABLE 3.1

Values of input parameters for turning experiments

TABLE 3.2

Experimental design using full factorial design of experiment

Factors Cutting Speed (m/min) Feed (mm/rev) Nose radius (mm)

Level 1 80 0.04 0.4

Level 2 116 0.12 0.8

Level 3 152 0.2 1.2

Sr. No. v m/min f (mm/rev) r (mm)

1 80 0.04 0.4

2 80 0.12 0.4

3 80 0.2 0.4

4 116 0.04 0.4

5 116 0.12 0.4

6 116 0.2 0.4

7 152 0.04 0.4

8 152 0.12 0.4

9 152 0.2 0.4

10 80 0.04 0.8

11 80 0.12 0.8

12 80 0.2 0.8

13 116 0.04 0.8

14 116 0.12 0.8

15 116 0.2 0.8

16 152 0.04 0.8

17 152 0.12 0.8

18 152 0.2 0.8

19 80 0.04 1.2

20 80 0.12 1.2

21 80 0.2 1.2

22 116 0.04 1.2

23 116 0.12 1.2

24 116 0.2 1.2

25 152 0.04 1.2

26 152 0.12 1.2

27 152 0.2 1.2


38

Table 3.2 shows experimental design for total 27 numbers of experiments based on full

factorial design of experiment for values of input cutting parameters reported in Table 3.1.

3.3 Experimental Work

Comprehensive details of workpiece, cutting tools, machine tool, instruments for

measurement and method of experimental work are systematically enumerated in this

section.

3.3.1 Workpiece

Workpiece material AISI D2 steel typically known as high chromium and high hardness

steel. Turning of various hard materials has been studied and reported by many

researchers. Hence, there is specific application of hardened AISI D2 steel in

manufacturing of dies, tools, automotive parts etc. Detail analysis on machining of

hardened AISI D2 steel is highly needed. This research is mainly concentrated on

investigation of turning of hardened AISI D2 steel. AISI D2 steel is high carbon high

chromium tool steel alloyed with molybdenum and vanadium. It is characterized by high

wear resistance, high compressive strength and good through hardening properties.

Normally it is machinable in annealed condition and will offer hardness to reach 57-59

HRC. Among different hardening processes, through hardening was applied to workpiece.

Cold worked through hardened AISI D2 steel with average hardness of 57 HRC was

obtained for experimentation. Through hardening of AISI D2 steel was done as per

following steps:

1) Annealing: Initially stress relieving process was applied by placing round bar inside

electric furnace and temperature was raised up to 650 °C for 1 Hrs. Then it was

cooled up to 350 °C.

2) Hardening: After annealing, round bar was place in salt bath furnace [salt bath =

liquid chemical (Sodium cyanide + Activator)] for 1000 °C until thoroughly soaked

up to 2 Hrs. Then it was oil quenched (Metaquench, 42 No. oil) up to 30 minutes.

3) Tempering: In the last stage, tempering of round bar was performed to get required

hardness in which round bar was placed in air furnace at 300 °C up to 3 Hrs. When

temperature reached up to 100 °C then round bar was removed from air furnace.

Experimental Work

39

Chemical compositions of AISI D2 steel are mentioned in Table 3.3.

TABLE 3.3

Chemical composition of AISI D2 steel in percentage

Physical properties of AISI D2 steel like Coefficient of thermal expansion at different

range of temperature, thermal conductivity, density, modulus of elasticity and poisson‘s

ratio are described in Table 3.4.

TABLE 3.4

Physical properties of AISI D2 steel [1, 2, 3]

Coefficient of thermal expansion 10-6

m/(m°K)

10.4 (20-100 °C); 11.5 (20-200 °C); 11.8 (20-300 °C);

12.3 (20-400 °C)

Thermal Conductivity W/(m°K) 16.7 (at 20 °C); 20.5 (at 350 °C); 24.5 (at 700 °C)

Melting point °C 1421

Density (kg/m3) 7700

Modulus of elasticity (GPa) 190-210

Poisson‘s ratio 0.27 – 0.30

Based on availability of spindle speed (RPM) of conventional lathe and findings of

literatures, it was necessary to select diameter of round bar for obtaining appropriate range

of cutting speed for experimental work. That range of cutting speed could be obtained

using diameter of 88 mm as per the relationship of cutting speed (m/min), spindle speed

(RPM) and diameter of round bar. So, raw material of AISI D2 steel round bar having

diameter (Ø) of 92 mm was selected and turned up to 88 mm diameter (Ø) to achieve

proper range of cutting speed (m/min). There were four round bars of AISI D2 steel with

different slots and grooves produced on it for accommodating 27 experimental sets to

perform turning and measurement of three dimensional forces of cutting, surface roughness

of machined part and flank wear of tool. Various grooves on workpiece of diameter (Ø) 88

mm and 380 mm length along with turning length of 262.5 mm was produced as shown in

Fig. 3.1.

C Si Mn Cr Mo V T

1.63 0.27 0.31 11.89 0.51 0.37 0.23


40

FIGURE 3.1 (a)

Detailed drawing of workpiece (AISI D2 steel) to perform full factorial design of experiments (all

dimensions are in mm)

FIGURE 3.1 (b)

Detailed drawing of workpiece (AISI D2 steel) for flank wear measurement at optimum cutting

conditions (all dimensions are in mm)

3.3.2 Cutting Tools

Three different CBN cutting tool inserts of ISO designation CNGA120404S01030A,

CNGA120408S01030A and CNGA120412S01030A (Sandvik make) having 0.4, 0.8 and

1.2 mm nose radius as shown in Fig. 3.2 were used for finish hard turning. Tool inserts

were fitted in standard tool holder of ISO designation DCLNR2525M12. In addition,

cutting tools and holder assembly provided orthogonal rake angle of -60, inclination angle

of -60, cutting edge angle of 95

0.

Experimental Work

41

FIGURE 3.2

CBN cutting tool insert of 0.4, 0.8 and 1.2 mm nose radius

3.3.3 Machine Tool

Turning of through hardened AISI D2 steel (57 HRC) was performed using heavy duty

lathe (model- HMT NH22). Selected machine tool is rigid enough and all the values of

depth of cut, feed and cutting speed selected for the experiments on turning of hardened

AISI D2 steel can be set on machine tool. Lathe (NH22) with proper foundation as per

suggestion given by original equipment manufacturer was used to increase rigidity and

performance of cutting process. Specifications of NH22 lathe is described in Table 3.5.

TABLE 3.5

Specifications of Lathe (NH 22 HMT make)

Sr. No. Description Size

1 Height of centers 220 mm

2 Swing over bed 500 mm

3 Swing over cross slide 270 mm

4 Swing in gap 720 mm

5 Distance between centers 1000 mm

6 Spindle nose/bore 53 mm

7 Range of spindle speed 16 from 40-2040 RPM forward

7 from 60-1430 RPM reverse

8 Spindle power 11 kw

9 Longitudinal feed 60 from 0.04-2.24 mm/rev

10 Cross feed 60 from 0.02-1.12 mm/rev

11 Pitch of lead screw 6 mm

12 Travel of tail stock sleeve 200 mm

13 Main motor power 7.5 kw


42

Cutting speed, feed and depth of cut is main cutting parameters to perform turning.

Experiment was performed using lathe (NH 22 HMT make) with wide range of spindle

speed from 40 – 2040 rpm, longitudinal feed from 0.04 – 2.24 mm/rev were available.

Here, it is required to measure output at cutting speed in m/min. So, spindle speed in rpm

can be converted in cutting speed (m/min) as per (3.1);

1000

dNv

(3.1)

Where, N = Spindle speed (RPM)

d = Workpiece diameter (mm)

Here, diameter of workpiece and spindle speed is selected to accommodate the range of

cutting speed from 80 – 152 m/min with the reference of various literatures as described in

chapter 2.

3.3.4 Surface Roughness Tester

Surface roughness of machined workpiece is measured using the surface roughness tester

SJ210 of Mitutoya make. Cut-off length and trace length and are selected as 0.8 mm and 5

mm respectively. Three different measurements of average surface roughness are taken

along the perimeter of machined AISI D2 steel and used for calculating average value of

surface roughness of machined workpiece. Detailed specifications of SJ210 are reported in

Table 3.6.

TABLE 3.6

Specifications of Surface roughness tester SJ210

Sr. No. Specifications Units

1 Method Differential inductance

2 Stylus Diamond TIP

3 TIP radius 5 µm (200 µ inch)

4 Make Mitutoyo

5 Model SJ-210

6 Measuring range -200 µm to + 150µm

7 Measuring Force 4mN(0.4gf)

8 Sampling length 0.8 mm x 5

Experimental Work

43

3.3.5 Tool Maker’s Microscope for Tool Wear Measurement

Maximum tool flank wear land length can be measured at some regular interval of cutting

length using tool maker‘s microscope having magnification of 30X. Tool flank wear can

be measured along the faces of nose radius. Some specifications of tool maker‘s

microscope are described in Table 3.7.

TABLE 3.7

Specifications of tool maker’s microscope

3.3.6 Lathe Tool Dynamometer for Measurement of Cutting Forces

Various instruments based on strain gauge principle are used to measure cutting forces

during turning. In this experimental work, forces in cutting, radial and axial directions

were measured with the help of strain gauge type 3-channel lathe tool dynamometer having

resolution of 0.01 Kg and accuracy of ±5 percent. Input sensitivity of amplifiers was set

based on the output sensitivity of dynamometer. Output sensitivity of dynamometer was

set 2 mV/V on individual charge amplifier corresponding to axial force, cutting force and

radial force. Specification of lathe tool dynamometer is described in Table 3.8.

TABLE 3.8

Specifications of Lathe tool dynamometer

Sr.No Descriptions Specifications

1 Table Glass 90 mm diameter

2 Work stage 120x120 mm

3 Travel X & Y 0 to 25 mm with accuracy 0.005 mm/ 0.01 mm

4 Working distance 4‖

5 Illumination: Episcopic 12 V, 5W

6 Power required 220-230VAC, 50 Hz

7 Eyepiece 15X

8 Objective 2X

9 Magnification 30X

Sr. No. Descriptions Specification

1 ―EEE‖ make Lathe tool dynamometer 3 channel PRD-02

2 X- Force – Axial 0 to 200 kgs

3 Y- Force - Radial 0 to 200 kgs


44

3.3.7 Experimental Procedure

Workpiece material AISI D2 steel round bar of diameter (Ø) 92 mm was turned up to

diameter (Ø) 90 mm before hardening. After machining of the grooves as per the

dimensions shown in Fig. 3.1 to accommodate all total 27 experimental sets, heat treatment

of round bar was applied to gain required average hardness of 57 HRC. Hardened round

bars are shown in Fig. 3.3.

FIGURE 3.3

Work piece material AISI D2 steel after heat treatment

Hardened round bars were prepared for final experiments by finished turning up to

diameter (Ø) of 88.4 mm. Flow chart as shown in Fig. 3.4 depicts complete step by step

procedure followed for experiments on finish hard turning.

For experimental work as per described flow diagram, roundbar was fitted in four jaw

chuck and centering was checked by level indicator. For successive set up, three

dimensional lathe tool dynamometer was fitted in the place of tool post. Figure 3.5 shows

workpiece with diameter (Ø) of 88.4 mm prepared for experiment on turning of hardened

AISI D2 steel.

4 Z- Force - Tangential 0 to 200 kgs

5 Resolution 0.01 kgs

6 Accuracy ± 5%

7 Bridge type Foil type strain gauge 120/350

ohms

8 Digital indicator 3(1/2) Digital

9 Power 230 VAC / 50 Hz

Experimental Work

45

FIGURE 3.4

Flow diagram of complete experimental work

FIGURE 3.5

Prefinal size of AISI D2 steel round bar before starting of experiment


46

Figure 3.6 shows workpiece after finish turning up to diameter (Ø) of 88 mm. Total 27

experiments were performed as per the input parameter combinations reported in Table 3.2

on various slots as shown in Fig. 3.6.

FIGURE 3.6

Finish hard turning at different cutting conditions

Three dimensional forces of cutting were measured using lathe tool dynamometer mounted

on lathe as shown in Fig. 3.7.

FIGURE 3.7

Experiment set up of lathe tool dynamometer

Experimental Work

47

Average value of three different surface roughness readings were measured for each

experimental set along the perimeter of machined workpiece. Measurement of surface

roughness was obtained using surface roughness tester SJ210 of Mitutoya as shown in Fig.

3.8.

FIGURE 3.8

Measurement of surface roughness with the help of surface roughness tester SJ210

Cutting conditions corresponding to experiment number for which lowest value of surface

roughness is obtained is defined as optimum cutting condition. Round bar having detailed

description as per Fig. 3.1 (b) was used to measure surface roughness, three dimensional

cutting forces and tool flank wear. Cutting forces using lathe tool dynamometer as shown

in Fig. 3.9 and maximum tool flank wear length using tool maker‘s microscope as shown

in Fig. 3.10 were measured at optimum cutting conditions.

FIGURE 3.9

Turning up to 65 mm cutting length for flank wear measurement


48

Fresh surface on flank face of tool wears out gradually during metal cutting and new

surface comes in contact with workpiece material. That affects the surface quality of

workpiece while machining. Also, wear of flank face is primarily responsible for

increasing surface roughness as suggested by various literatures. So, it was essential to

evaluate flank wear. Tool wear of flank face was measured along the faces of tool nose

radius by making suitable fixtures in such a way that whole wear face can be directly

viewed through tool maker‘s microscope as shown in Fig. 3.10.

Systematic methods are applied for experimentation and results of three dimensional

cutting forces (i.e. in axial, radial and cutting directions), surface roughness of machined

part and tool flank wear are reported in successive chapters. It is very essential to quantify

the individual or simultaneous influence of cutting variables on measured outputs of hard

turning.

FIGURE 3.10

Flank wear measurement with suitable fixture using Tool maker’s microscope

Variation of three dimensional forces in cutting, surface roughness and flank wear should

be analyzed and their relationship with input conditions like cutting parameters and

geometry parameters can be formulated using effective analytical modeling. Analysis of

experimental results and development of analytical model are reported in chapter 4.

References

49

References

[1] http://www.viratsteels.com/aisi-d2.html

[2] https://www.azom.com/article.aspx?ArticleID=6214

[3] http://www.substech.com/dokuwiki/doku.php?id=tool_steel_d2

http://www.viratsteels.com/aisi-d2.html

https://www.azom.com/article.aspx?ArticleID=6214

Ch. 4 Results and Discussion

50

CHAPTER – 4

Results and Discussion

4.1 Overview

Experimental readings of three dimensional forces of cutting and average surface

roughness for different experimental run as presented in chapter 3 are reported and

discussed in this chapter. Further, optimum cutting condition based on the experimental

values of the surface roughness is reported. Results of progressive wear of tool flank face

and its influence on cutting forces and surface roughness of machined component are

presented and analysed.

4.2 Experimental Results Based on Various Cutting Conditions

Total 27 different cutting conditions based on three different values of cutting speed (v)

(i.e. 80, 116 and 152 m/min), three different values of feed (f) (i.e. 0.04, 0.12 and 0.2

mm/rev) and three different values of nose radius (r) (i.e. 0.4, 0.8 and 1.2 mm) were

selected for experiments on turning of hardened AISI D2 steel with CBN tools. For finish

hard turning of AISI D2 steel, small value of depth of cut of 0.2 mm is selected and kept

constant for all 27 experiments. Experimental readings of surface roughness of machined

AISI D2 steel and cutting forces in axial, radial and cutting directions are measured and

reported in the Table 4.1.

Feed, cutting speed and nose radius of CBN tools are found to be significantly affecting

forces. Effect of nose radius (r) and feed (f) on axial (Fa), radial (Fr) and cutting (Fc) forces

at different values of cutting speeds (v) of 80, 116 and 152 m/min are reported in Fig. 4.1,

4.2 and 4.3 respectively.

Experimental Results Based on Various Cutting Conditions

51

TABLE 4.1

Experimental readings of axial (Fa), radial (Fr) and cutting (Fc) force and surface roughness (Ra)

EFFECT OF CUTTING AND GEOMETRY PARAMETERS ON CUTTING

FORCES: Experimental results of axial force (Fa), radial force (Fr) and cutting force (Fc)

for all 27 experiments are reported in Table 4.1. From Fig. 4.1, 4.2 and 4.3 it can be seen

that value of three dimensional forces of cutting is significantly higher followed by radial

and axial force. Similar trends in relative values of forces are reported by Tang et al. [1]. Based on the experimental readings, it can be analyzed that nose radius significantly

affects the cutting forces. Cutting forces increases with increase of tool nose radius from

0.4 mm to 1.2 mm as force is directly proportional to contact area which increases with

increase in nose radius [2, 3]. Axial (Fa), radial (Fr) and cutting (Fc) forces increase with

Exp. No. v (m/min) f (mm/rev) r (mm) Fa (N) Fr (N) Fc (N) Ra (μm)

1 80 0.04 0.4 52.48 78.48 109.28 1.34

2 80 0.12 0.4 78.94 134.59 153.90 1.57

3 80 0.2 0.4 98.02 175.04 197.64 2.27

4 116 0.04 0.4 49.93 67.69 96.14 0.92

5 116 0.12 0.4 70.88 118.43 132.17 1.2

6 116 0.2 0.4 92.19 155.89 178.59 1.59

7 152 0.04 0.4 42.67 65.73 90.25 0.77

8 152 0.12 0.4 64.23 113.26 119.54 0.97

9 152 0.2 0.4 72.75 127.00 147.22 1.128

10 80 0.04 0.8 65.63 115.12 128.80 0.967

11 80 0.12 0.8 99.18 172.52 201.80 1.21

12 80 0.2 0.8 121.43 213.74 244.87 1.6

13 116 0.04 0.8 60.23 96.14 112.73 0.693

14 116 0.12 0.8 83.48 156.57 173.29 1.02

15 116 0.2 0.8 108.78 199.12 226.06 1.22

16 152 0.04 0.8 53.29 87.31 103.58 0.55

17 152 0.12 0.8 81.32 139.96 155.98 0.739

18 152 0.2 0.8 98.10 187.75 203.21 1.05

19 80 0.04 1.2 75.17 131.61 151.20 0.734

20 80 0.12 1.2 116.44 207.33 238.29 1.03

21 80 0.2 1.2 137.54 220.14 258.03 1.21

22 116 0.04 1.2 69.65 117.13 130.47 0.578

23 116 0.12 1.2 103.37 183.72 210.08 0.81

24 116 0.2 1.2 128.72 216.84 247.83 0.997

25 152 0.04 1.2 63.77 111.34 118.70 0.504

26 152 0.12 1.2 87.19 166.67 185.17 0.685

27 152 0.2 1.2 113.67 201.31 235.25 0.925


52

increase of feed from 0.04 to 0.2 mm/rev. From the experimental results, it is observed

that cutting forces are inversely proportional to cutting speed (v). At constant value of feed

(f) and nose radius (r), cutting forces decreases with the increase of cutting speed (v) from

80 m/min to 152 m/min. With increase of cutting speed (v), temperature of shear zone

increases. This leads to thermal softening of material that means yield strength of material

decreases, which reduces the chip tool contact length and chip thickness. As a

consequence, forces decreases [4, 5].

0

40

80

120

160

200

240

280

0.4 0.8 1.2

Force (

N)

Tool nose radius (mm)

Fa at f= 0.04 mm/rev

Fa at f=0.12 mm/rev

Fa at f=0.2 mm/rev

Fr at f=0.04 mm/rev

Fr at f=0.12 mm/rev

Fr at f=0.2 mm/rev

Fc at f=0.04 mm/rev

Fc at f=0.12 mm/rev

Fc at f=0.2 mm/rev

FIGURE 4.1

Influence of feed (f) and nose radius of tool (r) on axial (Fa), radial (Fr) and cutting (Fc) force at cutting

speed (v) = 80 m/min and depth of cut (d) = 0.2 mm

0

40

80

120

160

200

240

280

0.4 0.8 1.2

For

ce (

N)



Fa at f=0.12 mm/rev

Fa at f=0.2 mm/rev

Fr at f=0.04 mm/rev

Fr at f=0.12 mm/rev

Fr at f=0.2 mm/rev

Fc at f=0.04 mm/rev

Fc at f=0.12 mm/rev

Fc at f=0.2 mm/rev

FIGURE 4.2

Influence of feed (f) and tool nose radius (r) on axial (Fa), radial (Fr) and cutting (Fc) force at cutting


Experimental Results Based on Various Cutting Conditions

53

0

40

80

120

160

200

240

280

0.4 0.8 1.2

Force (

N)



Fa at f=0.12 mm/rev

Fa at f=0.2 mm/rev

Fr at f=0.04 mm/rev

Fr at f=0.12 mm/rev

Fr at f=0.2 mm/rev

Fc at f=0.04 mm/rev

Fc at f=0.12 mm/rev

Fc at f=0.2 mm/rev

FIGURE 4.3

Influence of feed (f) and tool nose radius (r) on axial (Fa), radial (Fr) and cutting (Fc) force at cutting


In order to understand the criticality of various input factors under consideration on cutting

forces, individual effect of these factors on cutting forces is analyzed in following section.

4.2.1 Percentage Contribution of Cutting Variables on Cutting Forces

To understand the effect of individual cutting condition under consideration such as feed

(f), cutting speed (v) and nose radius (r) on cutting forces, percentage contribution of these

parameters towards cutting forces are evaluated as shown in appendix - A.

In order to complete the ANOVA table, total sum of square, factor sum of square and

percentage contribution of each factor is required to be evaluated. Three dimensional

cutting forces were considered to evaluate the effect of cutting speed (v), feed (f) and nose

radius (r) with their different contribution on cutting forces in hard turning of AISI D2

steel. ANOVA was performed based on 95 % confidence level. Also, p-value of model of

cutting force, radial force and axial force was obtained less than 0.05. So, all input

parameters considered for the present study such as cutting speed (v), feed (f) and tool nose

radius (r) are statistically significant on cutting forces.

Percentage contribution of cutting speed (v), feed (f) and nose radius (r) on cutting, radial and

axial force can be evaluated using (A.1) – (A.10) as reported in appendix - A. Analysis of

variance (ANOVA) of three factors and three levels of cutting, radial and axial force are

reported as shown in Tables 4.2 – 4.4.


54

TABLE 4.2

Percentage contribution of nose radius, cutting speed and feed attributes to cutting force

Correction factor (CF) = 766785.0

Total sum of squares or corrected sum of squares (TSS) = 70606.55

Error (Se) = 2483.28

Percentage error (% Se) = 3.53

TABLE 4.3

Percentage contribution of nose radius, cutting speed and feed attributes to radial force



Error (Se) = 1044.94


TABLE 4.4

Percentage contribution of nose radius, cutting speed and feed attributes to axial force



Error (Se) = 509.22

Parameters Total sum Factor sum

of squares

S(v, f, r)

% contribution

P(v, f, r) Level 1 Level 2 Level 3

v 1683.81 1507.36 1358.90 5879.36 8.32

f 120445.4 273954.2 417617.5 45232.12 64.06

r 1224.73 1550.32 1775.02 17011.78 24.09


of squares

S(v, f, r)

% contribution


v 1448.57 1311.53 1200.33 3435.74 5.85

f 870.55 1393.05 1696.83 38815.72 66.12

r 1036.11 1368.22 1556.09 15406.82 26.25


of squares

S(v, f, r)

% contribution


v 844.83 767.24 676.99 1568.07 9.22

f 532.83 785.03 971.20 10756.69 63.28

r 622.10 771.44 895.52 4164.98 24.50

Influence of Cutting Conditions on Surface Roughness

55


Based on results of ANOVA as reported in Tables 4.2–4.4; percentage sum of square error

of model is observed to be 3.53, 1.78 and 3.00 for cutting, radial and axial force,

respectively. Table 4.2 shows that percentage contribution of cutting speed (v), feed (f) and

nose radius (r) on cutting force component (Fc) is 8.32, 64.06 and 24.09 respectively.

Percentage contribution of cutting speed (v), feed (f) and nose radius (r) on radial force

component (Fr) is 5.85, 66.12 and 26.25 respectively as shown in Table 4.3. Percentage

contribution of cutting speed (v), feed (f) and nose radius (r) on axial force component (Fa)

is 9.22, 63.28 and 24.50 respectively as shown in Table 4.4. Feed (f) is observed to be most

significant parameter influencing cutting force (Fc), radial force (Fr) and axial force (Fa)

followed by tool nose radius (r). While cutting speed (v) is observed to be having smaller

contribution on cutting forces compared to feed (f) and tool nose radius (r).

4.3 Influence of Cutting Conditions on Surface Roughness

Value of surface roughness (Ra) at various cutting speed (v), feed (f) and nose radius (r)

was measured at constant depth of cut of 0.2 mm during finish hard turning as shown in

Table 4.1.

FIGURE 4.4

Effect of cutting speed (v) and feed (f) on surface roughness at tool nose radius (r) = 0.4 mm and depth

of cut (d) = 0.2 mm

0.6

0.85

1.1

1.35

1.6

1.85

2.1

2.35

70 85 100 115 130 145 160

Su

rfa

ce r

ou

gh

nes

s (μ

m)

Cutting speed (m/min)

f = 0.04 mm/rev

f = 0.12 mm/rev

f = 0.2 mm/rev


56

FIGURE 4.5

Effect of cutting speed (v) and feed (f) on surface roughness at tool nose radius (r) = 0.8 mm and depth

of cut (d) = 0.2 mm

FIGURE 4.6

Effect of cutting speed (v) and feed (f) on surface roughness (Ra) at tool nose radius (r) = 1.2 mm and

depth of cut (d) = 0.2 mm

Figures 4.4 shows variation of average value of surface roughness (Ra) for different

combinations of cutting speed (v) and feed (f) values for hard turning of AISI D2 round bar

using tool nose radius (r) of 0.4 mm. Similarly, Fig. 4.5 and 4.6 shows the variation of

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

70 85 100 115 130 145 160

Su

rfa

ce r

ou

gh

nes

s (μ

m)


f = 0.04 mm/rev

f = 0.12 mm/rev

f = 0.2 mm/rev

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

70 85 100 115 130 145 160

Su

rfa

ce r

ou

gh

nes

s (μ

m)


f = 0.04 mm/rev

f = 0.12 mm/rev

f = 0.2 mm/rev

Influence of Cutting Conditions on Surface Roughness

57

average surface roughness (Ra) for different combinations of cutting speed (v) and feed (f)

values for turning of hardened AISI D2 steel using tool nose radius (r) of 0.8 mm and 1.2

mm respectively. Depth of cut (d) is kept constant as 0.2 mm for all the experiments.

Experimental values of surface roughness observed at different cutting speed (v) and feed

(f) combinations are found to be in the range of 0.77-2.27 µm, 0.55-1.6 µm and 0.504-1.21

µm in the turning of AISI D2 steel with CBN cutting tool having tool nose radius (r) of 0.4

mm, 0.8 mm and 1.2 mm respectively. From Fig. 4.4, it can be analyzed that surface

roughness (Ra) reduces with increase of cutting speed (v) at constant feed (f) of 0.04

mm/rev for hard turning of AISI D2 steel with CBN tool having nose radius of 0.4 mm.

Similar trends are observed for CBN tool having nose radius (r) of 0.8 and 1.2 mm as

shown in Fig. 4.5 and 4.6. From Fig. 4.4-4.6 it is observed that average surface roughness

(Ra) obtained in turning of hardened AISI D2 steel increases with increase of feed rate (f).

Further, it is also observed that average surface roughness (Ra) decreases with increase in

tool nose radius (r) from 0.4 mm to 1.2 mm. During machining, more grooves were

produced with the decrease of nose radius from 1.2 mm to 0.4 mm which deteriorated the

surface finish of machined part. [6]. Moreover, ANOVA (analysis of variance) is applied

using Minitab software to check the individual effect of each input variable under

consideration on average surface roughness (Ra). It shows that tool nose radius (r) is the

most significant parameter affecting average surface roughness (Ra) with percentage

contribution of 43.93. While cutting feed (f) and cutting speed (v) are observed to be with

percentage contribution of 31.90 and 24.17 towards average surface roughness (Ra).

4.3.1 Percentage Contribution of Cutting Variables on Surface Roughness

Analysis of variance (ANOVA) was used to evaluate percentage contribution of each

conditions like; cutting speed (v), feed (f) and nose radius (r) on surface roughness (Ra).

Detailed calculation is described in Appendix B. Experiment values of average surface

roughness (Ra) were used for calculation of percentage contribution of individual cutting

parameters using (B.1)–(B.10). Table 4.5 shows percentage contribution of cutting speed

(v), feed (f) and nose radius (r) on average surface roughness (Ra).

In order to complete the ANOVA table, factor sum of square and total sum of square were

calculated and percentage contribution of each factors was reported as shown in Table 4.5.

Values of surface roughness (Ra) was used to evaluate different contribution of cutting


58

speed (v), feed (f) and nose radius (r). ANOVA was performed based on 95 % confidence

level. Also, p-value is less than 0.05. So, all input parameters under consideration (i.e.

cutting speed (v), feed (f) and nose radius (r)) are said to be statistically significant on

surface roughness (Ra). Percentage deviation (error) of sum of square of model was 8.84.

Percentage contribution of cutting speed (v), feed (f) and nose radius (r) in average surface

roughness (Ra) is found to be 30.56, 34.34 and 26.26 respectively. It is observed that feed

(f) was most influencing parameter which affected surface roughness (Ra) than cutting

speed (v) and nose radius (r).

TABLE 4.5

Percentage contribution of nose radius, cutting speed and feed attributes to surface roughness



Error (Se) = 0.35


4.4 Tool Flank Wear at Optimum Cutting Condition

As per results reported in Table 4.1, lowest value of average surface roughness (Ra) of

0.504 µm was observed for cutting speed (v), feed (f) and nose radius (r) combination of

152 m/min, 0.04 mm/rev and 1.2 mm respectively. Also, it is convenient to take

measurement of flank wear of cutting tool insert having higher nose radius (r) (in this case

it is 1.2 mm) compared to other tools having a smaller nose radius. So, these cutting

parameters are used to measure tool flank wear length using a tool maker‘s microscope at

regular interval of 65 mm cutting length. Experimental results of surface roughness and

flank wear of tool of machined AISI D2 round bar and cutting forces are reported in Table

4.6.


of square

S(v, f, r)

% contribution


v 11.93 9.03 7.32 1.21 30.56

f 7.06 9.23 11.99 1.36 34.34

r 11.76 9.05 7.47 1.04 26.26

Tool Flank Wear at Optimum Cutting Condition

59

TABLE 4.6

Experimental readings of tool flank wear, surface roughness and cutting forces at optimum cutting

conditions

INFLUENCE OF FLANK WEAR ON THREE DIMENSIONAL CUTTING

FORCES AND SURFACE ROUGHNESS: From experimental readings of tool flank

wear, it can be seen that tool flank wear length increases with cutting length. Progressive

increase in flank wear length affects the cutting forces (axial, radial, cutting force

component) and average surface roughness (Ra). Liu et al. [2] concluded that friction

between workpiece and tool increases with increase of flank wear which leads to

generation of heat. So, friction and plastic deformation during machining leads to thermal

impact which causes increase of residual tensile stresses at machined surface and hence

cutting forces are increased that increase the compressive residual stresses. Overall,

increase of residual stresses and flank wear reduces the stability of machining process and

deteriorates the surface finish of machined component. Three components of forces and

average surface roughness (Ra) is observed to be increasing with increase in wear of flank

face of tool as presented in Fig 4.7 and 4.8 respectively. Also, Fig. 4.8 shows increase of

surface roughness at slower rate up to wear of 0.105 mm. After 0.105 mm wear land length

of flank face, surface roughness increases rapidly. This increase amount of flank wear

increases residual compressive stresses which deteriorate the surface finish of machined

part.

Also, effect of forces on surface roughness at optimum cutting conditions is analyzed as

shown in Fig. 4.9. Individual impact of axial, radial and cutting force component on

surface roughness of machined AISI D2 steel can be observed in Fig. 4.9.

Sr. No. Cutting length

(mm) Fa (N) Fr (N) Fc (N) Ra (μm) Flank wear (mm)

1 65 70.40 125.24 155.15 0.510 0.094

2 130 72.25 128.45 157.3 0.513 0.099

3 195 73.1 129.48 159.47 0.525 0.105

4 260 73 131.26 164.13 0.547 0.109

5 325 74.22 132.18 167.63 0.561 0.112

6 390 74.6 134.28 173.42 0.581 0.114

7 455 75.58 135.75 176.72 0.587 0.117

8 520 76.45 136.55 179.53 0.598 0.12


60

FIGURE 4.7

Effect of flank wear on cutting forces at optimum cutting conditions (cutting speed (v) = 152 m/min,

feed (f) =0.04 mm/rev and tool nose radius (r) = 1.2 mm)

FIGURE 4.8

Effect of flank wear on surface roughness at optimum cutting conditions (cutting speed (v) = 152

m/min, feed (f) =0.04 mm/rev and tool nose radius (r) = 1.2 mm)

60

75

90

105

120

135

150

165

180

195

0.09 0.095 0.1 0.105 0.11 0.115 0.12 0.125

Cu

ttin

g f

orc

es (

N)

Flank wear (mm)

Axial force (N)

Radial force (N)

Cutting force (N)

0.5

0.52

0.54

0.56

0.58

0.6

0.62

0.09 0.095 0.1 0.105 0.11 0.115 0.12 0.125

Su

rfa

ce r

ou

gh

nes

s(μ

m)

Flank wear (mm)

Surface roughness (μm)


61

FIGURE 4.9

Correlation of surface roughness and cutting forces at optimum cutting conditions (cutting speed (v) =

152 m/min, feed (f) =0.04 mm/rev and tool nose radius (r) = 1.2 mm)

Increase of axial, radial and cutting force raised the surface roughness due to increase of

flank wear during hard turning performed with constant value of feed, cutting speed, depth

of cut and tool nose radius of 0.04 mm/rev, 152 m/min, 0.2 mm and 1.2 mm respectively.

Figure (4.9) shows that force in cutting direction is more sensitive to surface roughness

than radial and axial force. Value of cutting force observed higher than radial and axial

force at optimum cutting conditions. When cutting forces increases, it increases the

compressive residual stresses in work surface that reduces the surface finish of machined

workpiece [2].

It is observed from the experimental readings that cutting forces increases with the increase

of flank wear with increase of cutting length. This increase amount of cutting forces

increases the surface roughness at optimum cutting conditions. So, it has been tried to

analyze the influence of flank wear on resultant of three dimensional forces as shown in

Fig. 4.10 and consequence of resultant forces on surface roughness as shown in Fig. 4.11.

Resultant of cutting forces was evaluated as per (4.1);

2 2 2( ) ( ) ( )resultant c r aF = F F F (4.1)

Figure 4.10 shows linear relationship of resultant forces and flank wear having R2 value of

0.9498. Also, Fig. 4.10 shows that resultant forces increases with increase of flank wear.

60

80

100

120

140

160

180

200

0.5 0.52 0.54 0.56 0.58 0.6 0.62

Cu

ttin

g f

orc

es (

N)


Axial force (N)

Radial force (N)

Cutting force (N)


62

Also, resultant cutting forces can be predicted using different values of flank wear based

on equation as shown in Fig. 4.10. Predicted value of resultant cutting forces was 510.29 N

at flank wear of 0.38 mm which is critical value of flank wear for tool rejection criterion as

suggested by Huang and Liang [7].

FIGURE 4.10

Effect of flank wear on resultant cutting forces at optimum cutting conditions (cutting speed (v) = 152

m/min, feed (f) =0.04 mm/rev and tool nose radius (r) = 1.2 mm) as per Table 4.6

FIGURE 4.11

Effect of resultant cutting forces on surface roughness at optimum cutting conditions (cutting speed (v)

= 152 m/min, feed (f) =0.04 mm/rev and tool nose radius (r) = 1.2 mm) as per Table 4.6

y = 1052.4x + 110.38

R² = 0.9498

210

215

220

225

230

235

240

0.090 0.100 0.110 0.120 0.130

Res

ult

an

t o

f cu

ttin

g f

orc

es (

N)

Flank wear (mm)

Resultant of cutting

forces

y = 0.0035x - 0.2425

R² = 0.9839

0.5

0.52

0.54

0.56

0.58

0.6

0.62

210 215 220 225 230 235 240

Su

rfa

ce r

ou

gh

nes

s (μ

m)

Resultant of cutting forces (N)


Linear (Surface roughness

(μm))


63

Resultant cutting forces increases with increase of flank wear as a results it deteriorates

surface finish at constant value of depth of cut, feed, cutting speed and nose radius of tool

that can be seen in Fig. 4.11. Figure 4.11 shows linear trend of surface roughness and

resultant forces having R2 value of 0.9839. Surface roughness increases with increase of

resultant cutting forces as shown in Fig. 4.11. Also, surface roughness can be predicted

using different values of resultant cutting forces based on equation given in Fig. 4.11. At

resultant force of 510.29 N which was evaluated based on tool rejection criterion of flank

wear, predicted value of surface roughness was 1.55 µm. This research is pertaining to

finish hard turning to obtain smooth surface finish with the comparison of grinding

process. Typical value of surface finish using grinding can be obtained up to 1.6 µm [8].

So, tool rejection criterion can be decided based on evaluated resultant cutting force 510.29

N and surface roughness of 1.55 µm for finish hard turning. It means above 510.29 N of

resultant cutting forces, surface roughness would increase beyond 1.6 µm and tool is said

to be rejected specifically for finish hard turning in comparison with grinding process.

This would be helpful to manufacturing industries to judge the tool performance directly

based on resultant cutting forces.

Experimental values of cutting forces and average surface roughness (Ra) as presented and

scrutinized in various sections of this chapter are used for empirical modeling of cutting

forces and average surface roughness.


64

References

[1] Tang L, Gao C, Huang J, Lin X, Zhang J(2014) Experimental investigation of the three-component forces

in finish dry hard turning of hardened tool steel at different hardness levels, The International Journal of

Advanced Manufacturing Technology, 70, 1721-1729.

[2] Liu M, Takagi J-i, Tsukuda A(2004) Effect of tool nose radius and tool wear on residual stress


[3] Chang C-S(1998) A force model for nose radius worn tools with a chamfered main cutting edge,


[4] Bouacha K, Yallese MA, Khamel S, Belhadi S(2014) Analysis and optimization of hard turning operation

using cubic boron nitride tool, International Journal of Refractory Metals and Hard Materials, 45, 160-178.

[5] Bartarya G, Choudhury S(2012) Effect of cutting parameters on cutting force and surface roughness


[6] Liu CR, Mittal S(1996) Single-step superfinish hard machining: feasibility and feasible cutting

conditions, Robotics and computer-integrated manufacturing, 12, 15-27.

[7] Huang Y, Liang SY(2005) Modeling of cutting forces under hard turning conditions considering tool


[8] http://www.engineershandbook.com/Tables/surfaceroughness.htm

Modeling of Cutting Forces

65

CHAPTER – 5

Model Development of Three Dimensional Forces

and Surface Roughness for Hard Turning

5.1 Overview

Experimental readings of cutting forces and average surface roughness obtained as per the

experimental planning are reported in Chapter 3 and discussed in Chapter 4. From the

analysis of experimental results, it was observed that variable cutting conditions like

cutting speed (v), feed (f) and tool nose radius (r) significantly affects the cutting forces

and average surface roughness (Ra). Models of three dimensional forces and surface

roughness are developed based on empirical method to establish relationship with variable

input parameters. This chapter describes modeling of three dimensional cutting forces

based on cutting conditions. Further forces model is extended considering the effect of

progressive flank wear. In foregoing sections of the chapter, modeling of average surface

roughness is presented. At the end, validations of developed models are reported.

5.2 Modeling of Cutting Forces

As discussed in Chapter 2, large amount of research is reported describing development of

cutting forces model using various statistical and analytical methods like ANOVA,

response surface methodology, thermo-mechanical modeling, improved Oxley machining

theory, extended Lee and Shaffer‘s force model, Waldorf‘s theory of worn tool etc. Two

dimensional force modeling techniques are quiet easy to understand. While complex

mechanisms of three-dimensional cutting forces are observed during hard turning as a

result of obliquity in cutting process.

Relevant force models were documented based on the influence of specific factors on

cutting forces. Cutting parameters along with tool geometries simultaneously affect the

tool performance and influence the forces in hard turning. Here, analytical and empirical

Ch. 5 Model Development of Three Dimensional Forces and Surface Roughness for Hard Turning

66

modeling of cutting forces and wear phenomenon of flank face for finish turning of

hardened AISI D2 steel using different CBN tool is presented. Developed model includes

the effect of various factors like cutting speed (v), feed (f), nose radius (r) and flank wear

of tool on three-dimensional forces.

Empirical relationship is developed for total cutting forces in two distinct ways. First part

includes force modeling based on input cutting conditions during hard turning. Whereas in

second part, forces due to wear is modeled based on Waldorf‘s extended three dimensional

model and tool wear progression.

5.2.1 Modeling of Cutting Forces Based on Cutting Conditions

Various mathematical models were developed based on friction and normal forces which

comprises the shear stresses and shear zone [1-3]. Authors developed model of three

dimensional cutting forces based on certain assumptions. Some simplifying assumptions

need to be considered because of difficulty in calculating effective shear angle due to

critical orientation, resulting into increased inaccuracy. This drawback can be reduced to

some extent by establishing the relationship with cutting parameters and simplifying the

mechanism considering only variable cutting conditions without using complex orientation

of cutting forces while turning of hardened material. Wide variety of cutting conditions

along with tool geometries of cutting tool inserts have been used as per development of

cutting forces and reliability of tool. Consideration of cutting forces is important as it has

greater influence on the performance of hard turning [4]. In this research, models of cutting

forces in cutting, radial and axial directions are developed based on varying amounts of

feed (f), cutting speed (v) and tool nose radius (r) at small value of constant depth of cut

(d). Different orientation of forces Fc, Fr, and Fa can be resolved in cutting, radial and axial

directions respectively.

Here, cutting forces along radial, axial and cutting direction are functionally related with

cutting speed (v), feed (f) and nose radius (r). Linear relationship can be observed

between experimental results of cutting forces and cutting conditions like; cutting speed

(v), feed (f) and tool nose radius (r). So, their functional relationship is assumed as per Eq.

(5.1);


67

0 1 2 3

0 1 2 3

0 1 2 3

c

r

a

F a a f a r a v

F b b f b r b v

F c c f c r c v

(5.1)

Empirical model of cutting forces finish turning of hardened AISI D2 steel using CBN tool

is developed based on cutting forces results for total 27 different experiments for cutting

speed, feed and nose radius combinations as reported in Table 3.2. Experiments as reported

in Table 3.2 are designed based on full factorial design of experiments based on three

different values of cutting speed (v) (i.e. 80, 116 and 152 m/min), feed (f) (i.e. 0.04, 0.12

and 0.2 mm/rev) and tool nose radius (r) (i.e. 0.4, 0.8 and 1.2 mm). Depth of cut was kept

constant as 0.2 mm. Hence, developed empirical model as per Eq. (5.1) is valid for the

range of cutting speed 80 - 152 mm/min, range of feed 0.04 - 0.2 mm/rev, range of nose

radius 0.4 - 1.2 mm and 0.2 mm depth of cut. Further, when even any one of the cutting

parameter out of speed, feed or depth of cut is set to zero, turning is not possible. Tool tip

of perfectly sharp tool (i.e. having zero mm nose radius) breaks immediately when turning

of the hardened material is attempted because of high value of thrust force.

Huang and Liang [2] developed three dimensional oblique mechanistic force model as a

function of pressure coefficients, uncut chip thickness, width of cut, feed, rake angle and

side cutting edge angle. It means, there would be no effect of variation of cutting speed on

tool forces that contradicts with the work reported by Bouacha et al. [5]. Equation (5.1) can

predict three dimensional cutting forces using known values of cutting speed (v), feed (f)

and nose radius (r) which can easily be implemented.

Here, evaluation of constants used in (5.1) and validation of developed model need to be

performed for effective prediction of cutting forces based on cutting conditions.

DETERMINATION OF CONSTANTS AND VALIDATION OF FORCE MODEL

USING DIFFERENT EXPERIMENTAL SETS: For model presented in (5.1), constants

aj, bj and cj were evaluated based on total 27 numbers of experimental readings (as per full

factorial design experiments) as shown in Table 4.1. Values of these model constants can

be seen in Table 5.1. Forces model (5.1) was validated using another set of experiments.

For validation, combination of cutting speed and feed were different than reported

experimental sets in Table 4.1 which was used for development of model.


68

TABLE 5.1

Model constants evaluated using 27 experimental readings as per Table 4.1

TABLE 5.2

Experimental value of cutting (Fc exp), radial (Fr exp) and axial (Fa exp) force at different cutting

conditions

Table 5.2 represents the combinations of cutting speed, feed and tool nose radius used for

validation experiments along with measured values of cutting force, radial force and axial

force.

Three dimensional cutting forces were evaluated by developed empirical model and

compared with a wide range of experimental force data as reported in Table 5.2. Figure

5.1, 5.2 and 5.3 shows experimental and predicted values of cutting (Fc), radial (Fr) and

axial (Fa) force respectively. Also, error bars are plotted in Fig. 5.1, 5.2 and 5.3 having percentage errors of ± 7.2, ± 7.6 and ± 6.2, respectively. Values of all experimental and

predicted forces are observed within this range of error which shows closeness of

experimental and prediction values.

j = 0 j = 1 j = 2 j = 3

aj 90.74 623.29 76.42 -0.50

bj 64.48 573.80 72.21 -0.38

cj 47.91 304.43 37.97 -0.25

Exp.

No. v (m/min) f (mm/rev) r (mm) Fc exp (N) Fr exp (N) Fa exp(N)

1 81 0.05 0.8 137.91 113.15 68.67

2 153 0.05 0.8 99.23 88.47 57.53

3 117 0.06 1.2 155.15 134.53 85.1

4 153 0.07 1.2 142.15 123.34 72.3

5 117 0.05 0.4 91.48 72.67 45.24

6 153 0.06 0.4 78.67 64.91 39.43


69

FIGURE 5.1

Experimental and predicted value of cutting force based on different cutting conditions (cutting speed

(v), feed (f) and nose radius (r) as reported in Table 5.2)

Error variation of experimental and predicted value of cutting force (Fc), radial force (Fr)

and axial force (Fa) are found to be in the range of -2.56 to -7.16, -4.37 to -7.59 and -6.15

to 6.33 percentages respectively. It can be seen that all the predicted results of cutting,

axial and radial forces shows reasonable agreement with the measured value. Three

component of cutting forces are affected not only by different cutting parameters as

describe previously but also depend on effective cutting area which includes faces of front

end associated with nose radius and side cutting edge of the tool during oblique cutting.

60

80

100

120

140

160

180

0 1 2 3 4 5 6 7

Cu

ttin

g f

orc

e (N

)

Exp. No.

Fc exp (N)

Fc pred (N)


70

FIGURE 5.2

Experimental and predicted value of radial force based on different cutting conditions (cutting speed


FIGURE 5.3

Experimental and predicted value of axial force based on different cutting conditions (cutting speed


Wear land of flank face increases with the increase of cutting length in turning. Forces are

increased as contact area increases due to flank wear of tool. Thus, it is essential to

60

80

100

120

140

160

0 1 2 3 4 5 6 7

Ra

dia

l fo

rce

(N)

Exp. No.

Fr exp (N)

Fr pred (N)

30

40

50

60

70

80

90

0 1 2 3 4 5 6 7

Axia

l fo

rce

(N)

Exp. No.

Fa exp (N)

Fa pred (N)


71

inculcate the effect of tool flank wear in modeling of three dimensional cutting force

modeling.

5.2.2 Modeling of Cutting Forces Considering Progressive Flank Wear of Tool

In hard turning, a phenomenon of tool flank wear is observed on tool flank face. After a

turning, flank wear is developed and the friction is increased between tool and workpiece

[6, 7]. So, effective contact area and associated cutting forces are varied simultaneously.

These cutting forces need to be evaluated in the correlation with flank wear of tool. Figure

5.4 shows development of progressive flank wear in continuous machining. Tool flank

wear developed along tool flank face is modeled by considering depth of cut smaller than

nose radius [2].

Development of flank wear (Vb) is indicated along the cutting edge LMN as shown in Fig.

5.4(a) and (b). Its effect on three dimensional forces is shown in Fig.5.4 (c). Component of

cutting force (δFcw) and resultant force (δFarw) of other two forces (axial and radial force)

due to the wear is shown in Fig. 5.4 (a) and (c). Cutting force (Fcw), radial force (Frw) and

axial force (Faw) due to flank wear can be determined based on (5.2).

0LMN

LM MN

π/2

0 π/2 0

LM MN

= =

π= sin + cos -

2

π= sin + cos - (5.2)

2

π= - cos + sin -

2

= -

2 b

1

b 2 b

1

θ V

cw cw wθ

rw arw arw

V θ V

w wθ

aw arw arw

F δF r τ (z) dz dθ

F δF θ δF θ

r σ (z) θ dz dθ r σ (z) θ dz dθ

F δF θ δF θ

r

π/2

0 π/2 0

π cos + sin -

2

b 2 b

1

V θ V

w wθ

σ (z) θ dz dθ r σ (z) θ dz dθ

Where, -1 -1cos sin1 2θ = (f / (2r)) and θ = π - ((r - d) / r)


72

d

Vb

L M

N

Y

X

O

(a)

(b)

Fcw

Z

Fcw

Faw

Frw

Feed direction

Frw

Farw

Faw

(c)

FIGURE 5.4

Tool flank wear geometry; (a) cutting force component in z direction, (b) effective flank and nose wear,

(c) resultant force component of x and y direction

Also τw and σw are shear stress and normal stress along the tool flank face. Normal stress

(σw) and shear stress (τw) can be evaluated based on slip line field theory [2, 8]. In hard

turning, high temperature and stresses are developed in tool flank face. So, plastic flow

between workpiece and flank face of tool is initiated at critical wear land Vb*. Here Vb <

Vb*, thus elastic contact is established as per Waldorf‘s theory.

For given shear stress k and shear angle, if elastic contact exists between flank face and

workpiece then shear stress (τw) is modeled as:


73

00

0

0

0

, 0 1( )

, 1w

w b b

for xx

for V x V

(5.3)

Where, 0 cos(2 2 )k

1 1sin 2 sin( )sin( ) , 0.5cos ( )p p p pp m

Here, Waldorf‘s worn tool force model has been modified and fraction of progressive flank

wear and critical flank wear is considered to evaluate the normal stress (σw) along tool

flank face as shown in (5.4).

2

= b

w 0

b

Vσ σ

*V

(5.4)

Where, 0 1 2 2 2 sin(2 2 )2

k

Modeling of cutting forces due to flank wear is derived in the (5.2) to predict forces due to

flank wear progression. Equation (5.3) and (5.4) are used for determination of normal and

shear stress along the worn face tool as per slip line field theory. The friction factor mp

assumed to be unity due to the adhesiveness at the tool cutting edge. Raised prow of

material ahead of cutting is dependent on frictional stresses. For simplification of the slip-

line field theory, variable prow angle (p) is assumed zero as recommended by Waldorf. In

this analysis, An elastic contact was assumed between work surface and tool flank face

before tool failure [2, 8]. Critical wear land (Vb*) is taken as 0.38 mm as suggested by

Smithey et al. [9] for steel material. Shear angle (Ø) is evaluated as 10.14° using the

oblique cutting theory suggested by Lal [10]. Shear flow stress (k) is evaluated as 636.74

MPa using thermo-mechanical modeling based on Johnson–Cook law as presented by

Moufki et al.[1].

Cutting force components in cutting, radial and axial directions due to flank wear (i.e. Fcw,

Frw and Faw) were evaluated based on model (5.2) and plotted as shown Fig. 5.5. Flank

wear (Vb) is observed to be significantly affecting cutting force (Fcw) component. Whereas,

Influence of flank wear (Vb) on radial force (Frw) and axial force (Faw) component is

observed to be moderate to marginal.


74

FIGURE 5.5

Cutting forces in cutting (Fcw), radial (Frw) and axial (Faw) directions due to tool flank wear evaluated

based on progressive flank wear modeling

5.2.3 Evaluation of total cutting forces and its comparison with predicted values

In the hard turning, forces are influenced by actual orientation of tool, cutting condition

and flank wear of tool. So, as per (5.5), total cutting force (Fct), total radial force (Frt) and

total axial force (Fat) are the summation of the forces developed based on cutting

conditions (model (5.1)) and flank wear (model (5.2)).

ct c cw

rt r rw

at a aw

F F F

F F F

F F F

(5.5)

Equation (5.5) represents total cutting forces based on cutting conditions as per (5.1) and

forces develops due to progressive wear of flank face in cutting, radial and axial as per

(5.2). Validation of force model considering flank wear (Vb) as per (5.5) for machining

parameters (v, f and d), tool nose radius (r) and cutting length as per Table 4.6 is presented

in Fig. 5.6 – 5.8. For comparison of experimental and prediction value of cutting forces,

error bars were used in Fig. 5.6 – 5.8. Error bars were set as 9.0, 2.4 and 6.7 percent based

on error obtained between predicted and experimental values of total cutting force (Fct),

total radial force (Frt) and total axial force (Fat) respectively.

0

5

10

15

20

25

30

35

40

45

50

55

0.09 0.095 0.1 0.105 0.11 0.115 0.12 0.125

Cu

ttin

g f

orc

es d

ue

to w

ear

(N)

Tool flank wear (mm)

Cutting force due to wear (Fcw)

Radial force due to wear (Frw)

Axial force due to wear (Faw)


75

FIGURE 5.6

Comparison of total cutting force (Fct) considering flank wear (Vb)

FIGURE 5.7

Comparison of total radial force (Frt) considering flank wear (Vb)

150

155

160

165

170

175

180

185

0.09 0.095 0.1 0.105 0.11 0.115 0.12 0.125

To

tal

cu

ttin

g f

orc

e (F

ct)

N


Experimental

Prediction

120

122

124

126

128

130

132

134

136

138

0.09 0.095 0.1 0.105 0.11 0.115 0.12 0.125

To

tal

ra

dia

l fo

rce

(Frt

) N


Experimental

Prediction


76

FIGURE 5.8

Comparison of total axial force (Fat) considering flank wear (Vb)

Modeling of total cutting force component attributed to shear stress developed due to wear,

while total radial and axial force attributed to normal stress developed due to wear as per

(5.2). So, value of cutting force is higher than radial and axial force which is developed

due to flank wear. Error between predicted and measured values was found to be in the

range of -0.7 to -9.5, 0.57 to 2.36 and 2.24 to 6.40 percent for total cutting force (Fct),

radial force (Frt) and axial force (Fat) respectively.

5.3 Modeling of Surface Roughness

Surface roughness of machined component is of great interest in hard turning due to

advancement in the cutting tool area. Prediction of surface roughness is very difficult due

to complex mechanism of hard turning. Many researchers have developed the modeling of

surface roughness based on cutting parameters using various methods. It is practically

difficult to consider simultaneous effect of all possible factors affecting surface roughness

in modeling. Here, surface roughness modeling is done considering various cutting

parameters and tool geometry.

68

69

70

71

72

73

74

75

76

77

0.09 0.095 0.1 0.105 0.11 0.115 0.12 0.125

To

tal

axia

l fo

rce

(Fa

t) N


Experimental

Prediction

Modeling of Surface Roughness

77

5.3.1 Modeling of Surface Roughness Based on Cutting Conditions and Geometry

Cutting parameters like cutting speed (v), feed (f), depth of cut (d) and tool geometry

significantly affect the surface roughness of machined component. Singh and Rao [11]

analyzed surface quality with the help of RSM (response surface methodology) with

respect to machining parameters, effective rake angle and nose radius of tool. Response

surface methodology (RSM) was used by Aouici et al. [12] for modeling of surface

roughness as a function of machining parameters and workpiece hardness. Also, regression

analysis was used for modeling of surface roughness in relation with machining variables

like depth of cut, feed and cutting speed [13-16]. Reported research shows that value of

surface roughness reduces with the reduction in depth of cut [13, 17-19]. They concluded

that lower surface roughness value can be obtained using smaller value of depth of cut (0.2

mm). Basic formulation of surface roughness based on feed and tool nose radius is given in

(5.6)

2

32a

fR

r (5.6)

Where, f and r represents feed and nose radius respectively. As per (5.6), surface roughness

can be decrease only with decrease of feed and increase of tool nose radius. However there

are several problems with model presented in (5.6). Other variables like depth of cut and

cutting speed are not taken into account for effectiveness of prediction.

Some researchers [20, 21] reported models showing the correlation of cutting conditions

and surface roughness. It was found that variable cutting conditions affected the surface

finish of machined part. Linear and exponential empirical relationship was developed by

Fang and Safi-Jahanshahi [22] for surface roughness based on cutting speed (v), feed (f)

and depth of cut (d). Model presented by Fang and Safi-Jahanshahi [22] is limited to

cutting parameters (v, f, and d). Effect of tool geometries need to be considered as they

influence the surface finish of workpiece after machining. So, Surface roughness can be

formulated as function of independent parameters like cutting speed (v), feed (f), depth of

cut (d) and nose radius (r). Another possibility of variation of surface roughness is the

interaction of two parameters like cutting speed (v) – feed (f), cutting speed (v) – nose

radius (r), feed (f) – nose radius (r), cutting speed (v) – depth of cut (d), depth of cut (d) –

nose radius (r) and feed (f) – depth of cut (d). Here, efforts have been made to develop


78

model of surface roughness based on constant and smaller value of depth of cut with the

reference of various research work. Here variable cutting conditions are cutting speed (v),

feed (f) and tool nose radius (r). Simultaneous effect of all three variable parameters like

cutting speed (v), feed (f) and tool nose radius (r) on the surface roughness of hardened

AISI D2 steel can be observed in Fig. 4.4 - 4.6. Here, linear and exponential empirical

models suggested by Özel and Karpat [21] and Fang and Safi-Jahanshahi [22] are extended

to develop model of surface roughness based on simultaneous interaction effect of three

variables (v, f and r) at constant depth of cut as per (5.7).

31 20a vfr

cc ccR = v f r (5.7)

Now, (5.7) can be simplified as shown in (5.8).

1 2 3ln ln ln lnavfrR c v c f c r

(5.8)

Where, 0

ln c

Equation (5.7) shows functional relationship between surface roughness (Ravfr) and cutting

conditions (varying amount of cutting speed (v), feed (f) and nose radius (r) with constant

depth of cut (d)) for turning process.

Experimental investigation on assessment of surface roughness of machined part is

essential for any machining process as it defines surface quality of machined component.

Empirical model of surface roughness obtained in finish turning of hardened AISI D2 steel

using CBN tool is developed based on results of surface roughness for total 27 different

experiments for cutting speed, feed and nose radius combinations as reported in Table 3.2.

Experiments as reported in Table 3.2 are designed based on full factorial design of

experiments based on three different values of cutting speed (v) (i.e. 80, 116 and 152

m/min), feed (f) (i.e. 0.04, 0.12 and 0.2 mm/rev) and tool nose radius (r) (i.e. 0.4, 0.8 and

1.2 mm). Depth of cut was kept constant as 0.2 mm. Hence, developed empirical model as

per Eq. (5.7) is valid for the range of cutting speed 80 - 152 mm/min, range of feed 0.04 -

0.2 mm/rev, range of nose radius 0.4 - 1.2 mm and 0.2 mm depth of cut.

As per functional relationship, surface roughness will be zero if any one of the cutting

parameter out of speed, feed or nose radius is set to zero. When any one of the machining

Modeling of Surface Roughness

79

parameter is set as zero, there is no machining of material and turning process will not

exist.

5.3.2 Determination of Constants and Validation of Surface Roughness Model

After plotting results, nature of surface roughness can be observed and surface roughness

of workpiece at different cutting conditions in turning can be effectively predicted using

methods described in this section using (5.7) and (5.8). Various constants presented in

(5.7) and (5.8) were evaluated using experimental results obtained with full factorial design

of experiment as per cutting conditions reported in Table 4.1. Table 5.3 shows model

constants of surface roughness model based on total 27 experimental results as per full

factorial design of experiment. Effectiveness of developed model of surface roughness was

checked by comparing experimental and predicted value of surface roughness based on

different sets of cutting conditions like cutting speed (v); 81, 153 and 117 m/min and feed

(f); 0.05, 0.06 and 0.07 mm/rev as shown in Table 5.4.

TABLE 5.3

Model constants evaluated based on 27 experimental results as per Table 4.1

TABLE 5.4

Experimental values of surface roughness (Ra exp) using different sets of cutting conditions

i= 1 i= 2 i= 3 β= 4.08

ci -0.73 0.32 -0.39

Exp.

No. v m/min f (mm/rev) r (mm)

Ra exp

(μm)

1 81 0.05 0.8 0.98

2 153 0.05 0.8 0.57

3 117 0.06 1.2 0.631

4 153 0.07 1.2 0.541

5 117 0.05 0.4 0.98

6 153 0.06 0.4 0.83


80

FIGURE 5.9

Experimental and predicted value of surface roughness based on different cutting conditions (cutting

speed (v), feed (f) and nose radius (r) as reported in Table 5.4)

Experimental and predicted values of surface roughness were plotted along with error bars

having percentage errors of ±6.4 as shown in Fig. 5.9. Values of all experimental and

predicted values of surface roughness are observed to be within this range of error as

shown in Fig. 5.9. Predicted and experimental values of surface roughness (Ra pred) and

(Ra exp) respectively are found to be in close agreement with percentage error in the range

of –6.35 and +0.77 for validation set of experiments.

Empirical modeling of various cutting forces and surface roughness is reported in this

chapter. It is attempted to include all promising variables in the modeling during oblique

cutting of hard machining. Also, developed models are validated by comparing predicted

results of cutting forces and surface roughness with different sets of experiments. Overall,

outcome of this research work is reported in the chapter 6.

0.5

0.6

0.7

0.8

0.9

1

1.1

0 1 2 3 4 5 6 7

Su

rfa

ce r

ou

gh

nes

s (μ

m)

Exp. No.

Ra exp (μm)

Ra pred (μm)

References

81

References

[1] Moufki A, Devillez A, Dudzinski D, Molinari A(2004)Thermomechanical modelling of oblique cutting

and experimental validation, International Journal of Machine Tools and Manufacture, 44, 971-989.

[2] Huang Y, Liang SY(2005) Modeling of cutting forces under hard turning conditions considering tool


[3] Li K-M, Liang S(2007) Modeling of cutting forces in near dry machining under tool wear effect,


[4] Lalwani D, Mehta N, Jain P (2008) Experimental investigations of cutting parameters influence on

cutting forces and surface roughness in finish hard turning of MDN250 steel, Journal of materials processing

technology, 206, 167-179.

[5] Bouacha K, Yallese MA, Khamel S, Belhadi S(2014) Analysis and optimization of hard turning

operation using cubic boron nitride tool, International Journal of Refractory Metals and Hard Materials, 45,

160-178.

[6] Chinchanikar S, Choudhury S(2016) Cutting force modeling considering tool wear effect during turning

of hardened AISI 4340 alloy steel using multi-layer TiCN/Al2O3/TiN-coated carbide tools, The International

Journal of Advanced Manufacturing Technology, 83, 1749-1762.

[7] Liu M, Takagi J-i, Tsukuda A(2004) Effect of tool nose radius and tool wear on residual stress


[8] Waldorf DJ, DeVor RE, Kapoor SG(1998) A slip-line field for ploughing during orthogonal cutting,

Transactions-American Society Of Mechanical Engineers Journal Of Manufacturing Science And

Engineering, 120, 693-699.

[9] Smithey DW, Kapoor SG, DeVor RE(2001) A new mechanistic model for predicting worn tool cutting

forces, Machining Science and Technology, 5, 23-42.

[10] Lal G (1996) Introduction to machining science, New Age International.

[11] Singh D, Rao PV(2007) A surface roughness prediction model for hard turning process, The

International Journal of Advanced Manufacturing Technology, 32, 1115-1124.

[12]Aouici H, Yallese MA, Chaoui K, Mabrouki T, Rigal J-F(2012) Analysis of surface roughness and

cutting force components in hard turning with CBN tool: Prediction model and cutting conditions

optimization, Measurement, 45, 344-353.

[13] Özel T, Karpat Y, Figueira L, Davim JP(2007) Modelling of surface finish and tool flank wear in

turning of AISI D2 steel with ceramic wiper inserts, Journal of materials processing technology, 189, 192-

198.

[14] Thamizhmanii S, Saparudin S, Hasan S(2007) Analyses of surface roughness by turning process using

Taguchi method, Journal of Achievements in Materials and Manufacturing Engineering, 20, 503-506.

[15] Mehrban M, Naderi D, Panahizadeh V, Naeini HM(2008) Modelling of tool life in turning process using

experimental method, International journal of material forming, 1, 559-562.

[16] Suresh R, Basavarajappa S, Samuel G(2012) Some studies on hard turning of AISI 4340 steel using

multilayer coated carbide tool, Measurement, 45, 1872-1884.


82

[17] Lima J, Avila R, Abrao A, Faustino M, Davim JP (2005) Hard turning: AISI 4340 high strength low

alloy steel and AISI D2 cold work tool steel, Journal of Materials Processing Technology, 169, 388-395.

[18] Davim JP, Figueira L(2007) Machinability evaluation in hard turning of cold work tool steel (D2) with

ceramic tools using statistical techniques, Materials & design, 28, 1186-1191.

[19]Poulachon G, Bandyopadhyay B, Jawahir I, Pheulpin S, Seguin E(2004) Wear behavior of CBN tools

while turning various hardened steels, Wear, 256, 302-310.

[20] Asiltürk I, Çunkaş M(2011) Modeling and prediction of surface roughness in turning operations using

artificial neural network and multiple regression method, Expert Systems with Applications, 38, 5826-5832.

[21] Özel T, KarpatY(2005) Predictive modeling of surface roughness and tool wear in hard turning using

regression and neural networks, International Journal of Machine Tools and Manufacture, 45, 467-479.

[22] Fang XD, Safi-Jahanshahi H (1997) A new algorithm for developing a reference-based model for

predicting surface roughness in finish machining of steels, International Journal of Production Research,

35(1), 179-99.

Conclusions

83

CHAPTER – 6

Conclusions and Future Scope

6.1 Conclusions

This research comprises the empirical modeling of three dimensional forces and analysis of

effect of cutting speed (v), feed (f) and nose radius (r) on cutting force (Fc), radial force

(Fr) and axial force (Fa). Also, experimental values of surface roughness (Ra) obtained

based on various cutting conditions and tool nose radius (r) are used for development of

empirical model of surface roughness (Ra) of in the hard turning of AISI D2 steel using

CBN tools. From analysis and modeling of cutting tool forces and surface roughness (Ra),

following conclusions are drawn:

CUTTING FORCES:

Cutting forces decrease with increment of cutting speed (v). Influence of variation of

nose radius (r) on tool performance is clearly observed. When tool nose radius (r)

increases from 0.4 mm to 1.2 mm, cutting forces in axial, radial and cutting directions

are increased. Also cutting forces increases with increase of feed (f).

Empirical method is used to develop relationship between three dimensional cutting

forces and variable cutting conditions of hard turning. Complex oblique cutting process

is evaluated as simplified linear model which shows functional relationship of cutting

force (Fc), radial force (Fr), axial force (Fa) with variable cutting speed (v), feed (f) and

tool nose radius (r) in the hard turning of AISI D2 steel with CBN tools. So, it is useful

to identify input variable which affects cutting forces significantly.

Developed empirical model shows the functional relationship of feed (f), cutting speed

(v), nose radius (r) and cutting forces (Fc, Fr and Fa) as per following equation;

90.74 623.29 76.42 0.50

64.48 573.80 72.21 0.38

47.91 304.43 37.97 0.25

c

r

a

F f r v

F f r v

F f r v

Ch.6 Conclusions and Future Scope

84

Empirical model for progressive flank wear is developed to inculcate the effect of flank

wear on cutting forces. Based on the validation it was observed that, cutting forces can

be predicted more accurately by considering flank wear.

Error between predicted and measured values is found to be in the range of -0.7 to -9.5

percent, 0.57 to 2.36 percent and 2.24 to 6.40 percent for total cutting force (Fct), radial

force (Frt) and axial force (Fat), respectively. This shows effectiveness of developed

empirical models for prediction of cutting forces.

This research includes performance of hard turning in terms of cutting forces, variable

cutting parameters and different tool nose radius (0.4, 0.8 and 1.2 mm). Here, three

dimensional cutting forces are formulated to develop model which is useful to

industries (like Sandvik, Kyocera, American carbide tool company etc.) related to

manufacture of different CBN tools for hard turning for designing of CBN tools based

on variable nose radius. Also, it can be extended by adding some variables as per

specific requirement of industry in the developed model.

SURFACE ROUGHNESS:

Linear and exponential empirical relationship is found between the input variables

(cutting speed (v), feed (f), nose radius (r)) and surface roughness (Ra) of AISI D2 steel

during hard turning.

Surface roughness (Ra) decreases with reduction in feed (f) from 0.2 mm/rev to 0.04

mm/rev; whereas, surface roughness (Ra) decreases with increase in cutting speed (v)

from 80 m/min to 152 m/min. When tool nose radius (r) increases from 0.4 mm to 1.2

mm, surface roughness (Ra) is found to be decreasing. Lower surface roughness (Ra)

(0.504 µm) of machined part is achieved at lower feed (f), high cutting speed (v) and

large nose radius (r).

Developed empirical model shows the functional relationship of feed (f), cutting speed

(v), nose radius (r) and surface roughness (Ra) as per following equation;

ln 4.08 0.73ln 0.32ln 0.39lnavfrR v f r

Validation of developed model is performed using different sets of experiment and

found to be in reasonable agreement with experimental results of surface roughness

(Ra) with error variation of about –6.35 percent to 0.77 percent.

Overall, complete analysis of cutting forces and surface roughness (Ra) of machined AISI

D2 steel based on different cutting conditions along with tool geometries can be obtained.

Future Scope

85

Complex oblique cutting phenomenon is simplified in the modeling and various constants

used in models can be easily evaluated using MATLAB programming. Also, models of

cutting forces and surface roughness (Ra) are conceptually evaluated for effective

prediction of cutting forces and surface roughness (Ra) at different cutting conditions.

6.2 Future Scope

Turning length of hardened workpiece affects the performance of machining. if

length of round bar increase, it increases the overhung problem hence increases the

vibration of workpiece. In addition, there is always some effect of vibration of tool

that is presented during hard turning. So, Model of cutting forces and surface

roughness that is developed in this research can be extended by including the effect

of stated noise factors.

Effect of various hardness of material on surface finish and cutting forces can be

analyzed in hard turning. Also, variation of hardness of workpiece can be added in

developed modeling of surface roughness and cutting forces.

Appendices

86

APPENDICES

Appendix – A: Calculation of Percentage Contribution of Variable

Cutting and Geometry Parameters on Cutting Forces

Calculation of percentage contribution of individual cutting parameters; nose radius,

cutting speed and cutting feed on cutting forces is described as follows:

Total number of runs, n = 27

Total degree of freedom, ft = n-1 = 26

Three factors and their levels;

Nose radius (r): r1 = 0.4 mm, r2 = 0.8 mm, r3 = 1.2 mm

Cutting speed (v): v1 = 80 m/min, v2 = 116 m/min, v3 = 152 m/min

Feed (f): f1 = 0.04 mm/rev, f2 = 0.12 mm/rev, f3 = 0.2 mm/rev

Procedure to evaluate percentage contribution on cutting force component:

2( )( )

27

Sumof cutting forceCorrection factor CF

(A.1)

Total sum of Squares (or corrected SS)(TSS) = (Fc12+Fc2

2+……..+Fc27

2) – CF (A.2)

Sum of cutting forces developed due to nose radius, cutting speed, and feed

attributes to its individual level can be calculated as per following method;

Fcr1 = Sum of cutting force developed using nose radius r1 = 0.4 mm.



Fcv1 = Sum of cutting force developed using cutting speed v1 = 80 m/min.



Fcf1 = Sum of cutting force developed using feed f1 = 0.04 mm/rev.



Likewise, sum of radial and axial force can be evaluated based on above methods.

Factor sum of squares;

Sr =Fcr12 / Nr1 + Fcr2

2 / Nr2 + Fcr33/ Nr3 – CF (A.3)

Calculation of Percentage Contribution of Variable Cutting and Geometry Parameters on Cutting Forces

87

Sv = Fcv12 / Nv1 + Fcv2

2 / Nv2 + Fcv32 / Nv3 – CF (A.4)

Sf = Fcf12 / Nf1 + Fcf2

2 / Nf2 + Fcf32 / Nf3 – CF (A.5)

Error Se = TSS – (Sr+ Sv + Sf) (A.6)

Percentage of error (Se) = Se*100 / TSS (A.7)

Percentage contribution of each factor can be evaluated as per (A.8), (A.9) and (A.10).

% contribution of nose radius (Pr)= Sr X 100 / TSS (A.8)

% contribution of cutting speed (Pv)= Sv X 100 / TSS (A.9)

% contribution of feed (Pf)= Sf X 100 / TSS (A.10)

Appendices

88

Appendix – B: Calculation of Percentage Contribution of Variable

Cutting and Geometry Parameters on Surface Roughness

Calculation of percentage contribution of individual cutting parameters; nose radius,

cutting speed and cutting feed on surface roughness is described as follows:

Total number of runs, n = 27

Total degree of freedom, ft = n-1 = 26

Three factors and their levels;

Nose radius (r): r1 = 0.4 mm, r2 = 0.8 mm, r3 = 1.2 mm

Cutting speed (v): v1 = 80 m/min, v2 = 116 m/min, v3 = 152 m/min

Feed (f): f1 = 0.04 mm/rev, f2 = 0.12 mm/rev, f3 = 0.2 mm/rev

Procedure to evaluate percentage contribution on surface roughness:

2( )( )

27

aSumof RCorrection factor CF

(B.1)

Total sum of Squares (or corrected SS)(TSS) = (Ra12+Ra2

2+……..+Ra27

2) – CF (B.2)

Sum of surface roughness developed due to nose radius, cutting speed, and feed

attributes to its individual level can be calculated as per following method;

Ra r1 = Sum of surface roughness developed using nose radius r1 = 0.4 mm.



Ra v1 = Sum of surface roughness developed using cutting speed v1 = 80 m/min.



Ra f1 = Sum of surface roughness developed using feed f1 = 0.04 mm/rev.



Factor sum of squares;

Sr =Ra r12 / Nr1 + Ra r2

2 / Nr2 + Ra r33/ Nr3 – CF (B.3)

Sv = Ra v12 / Nv1 + Ra v2

2 / Nv2 + Ra v32 / Nv3 – CF (B. 4)

Sf = Ra f12 / Nf1 + Ra f2

2 / Nf2 + Ra f32 / Nf3 – CF (B.5)

Calculation of Percentage Contribution of Variable Cutting and Geometry Parameters on Surface Roughness

89

Error Se = TSS – (Sr+ Sv + Sf) (B.6)

Percentage of error (Se) = Se*100 / TSS (B.7)

Percentage contribution of each factor on surface roughness can be evaluated as per

(B.8), (B.9) and (B.10).

% contribution of nose radius (Pr)= Sr X 100 / TSS (B.8)

% contribution of cutting speed (Pv)= Sv X 100 / TSS (B.9)

% contribution of feed (Pf)= Sf X 100 / TSS (B.10)

List of Publications

90

List of Publications

1. Patel VD, Gandhi AH (2017) Analytical and Empirical Modeling of Wear and Forces of

CBN Tool in Hard Turning-A Review, Journal of The Institution of Engineers (India):

Series C, 98(4), pp.507-513.

2. Patel VD, Patel AR, Gandhi AH (2014) Analysis and prediction of tool wear, machined

surface roughness in Hard turning, International Journal for Scientific Research &

Development; Vol. 2, Issue 02, 2014, ISSN: 2321-0613

3. Patel V D, Patel AR, Gandhi AH (2014), Analysis and Prediction of Tool wear,

Machined Surface Roughness and Force Components in Hard Turning – A Review, 2nd

National Conference on Thermal Fluid and Manufacturing science (TFMS -2014) (ISBN:

978-81-927693-3-2).

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