Mathematical Modeling of Hard Facing Low Carbon Steel With Corrosive Nickel Based Alloy by Gmaw
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Transcript of Mathematical Modeling of Hard Facing Low Carbon Steel With Corrosive Nickel Based Alloy by Gmaw
MATHEMATICAL MODELING OF HARDFACING LOW CARBON
STEEL WITH CORROSIVE NICKEL BASED ALLOY BY GMAW
Under the Guidance of
Prof. C. Bhagyanathan AP/MFG
Assistant Professor
ByS. Santhosh(1066008)
INTRODUCTION
Corrosion and Wear are the major problems in metallic components. Wear occurs in the sliding contacts due to dynamic loading.
Both has drastic effects on the applications and costs on metallic components.
PROBLEM IDENTIFICATION
• Wear is the drastic effect on metal to metal contact parts so the life span of the part is short according to its service condition.
• Replacing the worn-out parts to new parts in all the time is not economic for industries.
• Most of the machine parts has weight to strength ration constrains within this limits the material property should be enhanced.
PROBLEM DEFINITION
• To create mathematical model for bonding Chromium-Cobalt alloy with Low Carbon Steel for GMAW process
• To optimize GMAW process parameters
• Validate the result by applying conformity test, corrosion test and wear test.
METHODOLOGY
Problem Identification
Literature Survey
Development of GMAW Setup
Development of Mathematical models for the prediction of weld bead geometry
LITERATURE SURVEY
Extended Abstract• The defect free deposits can be made without any preheating
by the GMAW process and the deposits has a more uniform.
1Effect of Welding Parameters on the Microstructure of Stellite-6 Deposits
Key words• GMAW, Microstructure, Stellite-6
Interception• Study on the GMAW process
Extended Abstract• Constant current characteristics were typically
advantageous for automatic welding, to provide sufficient accuracy and repeatability in current level from weld to weld.
2 Basics to know when choosing a GMAW and GTAW power source
Key words• GMAW, GTAW, Accuracy, Repeatability
Interception• Power supply characteristics of GMAW process
Extended Abstract• GMAW is the best suited for hardfacing small parts as it
produces high quality deposits.
3 Hardfacing – Past, Present, Future
Key words• GMAW, Hardfacing, Quality
Interception• Study the importance of hardfacing
Extended Abstract• Welding variables such as welding current, filler rod feed
rate, welding speed and even current mode have effect on surfacing deposit irrespective of process.
5 Hardfacing International Welding Journal
Key words• Welding parameter
Interception• Study on effect of welding variables on deposit rate
PARAMETERS
PARAMETERS
ParameterArc
Voltage
Wire Feed Rate
Welding Speed
Nozzle to Plate Distance
Unit Volt m/min cm/min cm
Notation V F S D
Level1 37 7 24 1.5
-1 27 4 10 1
DOE MATRIX
Trail No.
Process variables
Arc Voltage (V) Wire feed rate (F)Welding speed
(S)Nozzle to plate
distance (D)
01 -1 -1 -1 -1
02 1 -1 -1 -1
03 -1 1 -1 -1
04 1 1 -1 -1
05 -1 -1 1 -1
06 1 -1 1 -1
07 -1 1 1 -1
08 1 1 1 -1
09 -1 -1 -1 1
10 1 -1 -1 1
11 -1 1 -1 1
12 1 1 -1 1
13 -1 -1 1 1
14 1 -1 1 1
15 -1 1 1 1
16 1 1 1 1
RESPONSE
Trail No.Process variables Bead parameters
V F S D BW BH BP Di %
01 -1 -1 -1 -1 10.17 3.50 1.19 19.19
02 1 -1 -1 -1 9.51 4.40 1.06 25.35
03 -1 1 -1 -1 11.02 3.95 1.31 19.48
04 1 1 -1 -1 7.01 3.19 1.04 24.97
05 -1 -1 1 -1 9.52 2.74 1.29 24.50
06 1 -1 1 -1 7.85 3.64 1.16 31.92
07 -1 1 1 -1 9.97 3.19 1.41 24.18
08 1 1 1 -1 8.78 4.10 0.78 30.66
09 -1 -1 -1 1 10.89 3.65 1.03 15.95
10 1 -1 -1 1 9.62 4.55 0.90 21.97
11 -1 1 -1 1 11.13 4.10 1.15 16.57
12 1 1 -1 1 7.13 3.34 0.88 21.96
13 -1 -1 1 1 9.64 2.89 1.13 20.76
14 1 -1 1 1 7.97 3.79 1.00 28.01
15 -1 1 1 1 10.48 3.34 1.25 20.89
16 1 1 1 1 10.17 3.50 1.19 27.24
MATHEMATICAL MODEL
The response function representing any weld bead dimension can be expressed as,
Y = f (V, S, F, D)Where,
Y = Response function.b0, bi = Regression co-efficient.
Xi = Parameters or variables.
K
Y = b0 + Σ bi Xi
i=1
MATHEMATICAL MODEL
For four factors the selected polynomial (regression) equation could be expressed as:
Y = b0 + b1V + b2 F + b3 S
+ b4 D
REGRESSION COEFFICIENT
Coefficient Due to
Value
BW BH BP Dilution
b0 Combined effect of all parameters (Main effect) 2.450 4.801 0.345 5.436
b1 Arc Voltage 0.204 – 0.0450 0.025 0.631
b2 Wire Feed Rate 0.240 0.1500 0.042 – 0.070
b3 Welding Speed – 0.091 – 0.054 0.007 0.381
b4 Nozzle to Plate Distance 0.482 0.303 – 0.32 – 6.725
FINAL MATHEMATICAL MODELS
The final mathematical models as determined by the above analysis are presented below:
BW = 2.450 + 0.204 V + 0.240 F – 0.091 S + 0.482 D
BH = 4.801 – 0.045 V + 0.15 F – 0.054 S + 0.303 D
BP = 0.345 + 0.025 V + 0.042 F + 0.007 S – 0.32 D Dilution = 5.436 + 0.631 V – 0.070 F + 0.381 S – 6.725 D
INFLUENCE OF PROCESS PARAMETERS ON BEAD WIDTH.
• Arc Voltage, Wire Feed Rate and Nozzle to Plate Distance shows an positive influence on the bead width.• Welding Speed shows an negative influence on the bead width.• From the positive influencers the Nozzle to Plate Distance Plays major role
INFLUENCE OF PROCESS PARAMETERS ON BEAD HEIGHT
• Wire Feed Rate and Nozzle to Plate Distance shows an positive influence on the bead width.• Welding Speed and Arc Voltage shows an negative influence on the bead width.• From the positive influencers the Nozzle to Plate Distance Plays major role
INFLUENCE OF PROCESS PARAMETERS ON BEAD PENETRATION
• Arc Voltage, Wire Feed Rate and Welding Speed shows an positive influence on the bead width.• Nozzle to Plate Distance shows an negative influence on the bead width.• From the positive influencers the Nozzle to Plate Distance Plays major role
INFLUENCE OF PROCESS PARAMETERS ON DILUTION
• Arc Voltage, and Welding Speed shows an positive influence on the bead width.• Wire Feed Rate and Nozzle to Plate Distance shows an negative influence on the bead width.• From the positive influencers the Nozzle to Plate Distance Plays major role
CONCLUSION The primary objective of this dissertation is to develop
mathematical models for improving the weld bead quality using GMAW process, for FW-2 hardfacing on low carbon valve.
The mathematical models were developed using regression analysis and four factor two level design matrix is effectively used.
Mathematical models were developed for the following responses like Bead Height (BH), Bead Reinforcement (R), and Bead Width (W), The responses were related with process parameters, Arc Voltage (V), Wire Feed Rate (F), Welding Speed (S) and Nozzle to Plate Distance (D).
The Mathematical model indicates, the influence of Arc Voltage, Feed Rate, Welding Speed and Nozzle to Plate Distance on Bead Height, Bead Reinforcement and Bead Width
FUTURE RESEARCH FOR PHASE - II
This research has focused on developing mathematical modeling for GMAW process for Hardfacing FW-2 alloy on low carbon steel material.
The study can be extended to optimize the parameter. Study the corrosion and wear resistance of the low
carbon steel after hardfacing with FW-2 alloy. Future research studies need to investigate the different
alloys or processes which can be employed for depositing hardfaced layers.
REFERENCES
1. Albert S.K, Gowrisankar I, Seetharaman V, and Venkatesan S, “Effect of Welding Parameters on the Microstructure of Stellite-6 Deposits”, Proceeding of National Welding Seminar, IIW, Bangalore., Nov. 26-28, pp A1- A7.
2. Dennis Destefan, “Basics to know when choosing a GMAW and GTAW power source”, Welding Journal, pp 67-72.
3. Barr L.C. and Rogers C.E., “ Hardfacing – Past, Present, Future”, Welding Journal, pp 968-974.
4. Foroulis Z.A, “ Guidelines for the selection of hardfacing alloys for Sliding Wear Resistance Application”, TMS –AIME, New York, pp. 203-218.
5. Quaas J.F., “Hardfacing International Welding Journal”, pp.175-182.