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Quality Management
N.K.Agarwal
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Quality Management
Product and service quality can be definedas The total composite product & service
characteristics of marketing, engineering,
manufacturing and maintenance Through which the product and service in use
Will meet the expectations of the customer
Quality to industry means best for
satisfying customer conditions Important among these conditions are
The actual end use
The selling price of product/service
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Quality features of a Product
Product features Performance
Reliability
Durability
Ease of use
Serviceability
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Quality features of Service
Quality of a service judged by Reliability
Availability
Credibility
Security
Competence of staff
Understanding of customer needs
Responsiveness to customers
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Courtesy of staff
Comfort of surroundings
Communication between participants
Associated goods provided with the service
Freedom from deficiencies
Service free of errors during original andfuture service transactions
Sales, billing and other business processes
free of errors
Quality features of Service
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Quality Control (Q.C.)
Procedures for meeting the goals Generally 4 steps
Setting standards
Appraising conformanceActing when necessary
Planning for improvement
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Statistical Quality Control (SQC)
Application of the statistical techniquesto accept or reject products already
produced or to control the process, andtherefore product quality while the partis being made.
The later process called process control
Former is named as acceptance sampling
These are two prominent techniques ofQC
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SQC for Process Control
Based on probability theory
During manufacturing of identical parts, some are a little
large, some a little small but the average will be most frequent
The smaller and bigger sizes are extremes from the average
Bell or normal shaped curve obtained when frequency or
counts of items by size plotted with size on the horizontal
scale and count on the vertical scale
In practice, SQC for process control done throughcontrol charts
First developed by Dr. Walter A. SHEWART of BellTelephone Labs during 1930s
Horizontal extensions of the bell shaped curve
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Bell Shaped Curve
SIZE
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Control Chart
TIME
LCL
CL AVERAGE QUALITY
UCL
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Control Charts
Types Control charts for variables
Control charts for attributes Variables
Quality characteristics that can be measured on acontinuous scale ex: diameter of a shaft
Attributes Quality characteristics which can be classified into
one of the categories namely good or bad,defective or non- defective ex: an ammunition
bullet
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Control Charts
Center line (CL): average quality
Upper and Lower control limits (UCL & LCL): also
called tolerance limits
Process is said to be stable or under control if the
quality of samples checked and variations plotted on
the charts show the values within UCL and LCL
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Control Charts
Usually two types of information available from the
charts
Whether the process is running under stable condition or not
i.e. Whether the process is under state of statistical controlor not
Whether the process is meeting the desired quality
standards or not.
If statistical control does not exist, it has to be
established through technical control
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Acceptance Sampling Techniques
Best alternative of estimating quality of incoming/out
going lots when 100% inspection not practical
Sampling inspection necessary because of high cost
of 100% inspection or destructive nature of
inspection or testing Based on the premise that a sample represents the
whole lot from which the sample is drawn
Random sampling provides each element an equalchance of being selected and permit logical
inferences to be made about the lot quality based on
sample evidence
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Acceptance Sampling
Lot accepted or rejected based on the
number of defects found in the sample
No need to inspect the entire lot Risks of accepting bad lots or rejecting good
lots always associated while making
decisions based on sample evidence
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Errors in Sampling
Type-I error An error when a sample from the output of a
process may lead to conclusion that the process
is out of control, when in fact, it is operating asintended: Producers risk ()
Type-II error An error when sample leads to conclusion that
the process is satisfactory , when in fact, theprocess is not working as intended: Consumers
risk ()
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Total Quality Control
Total Quality Control (TQC) An effective system for integrating
The quality development,
Quality maintenance and Quality improvement efforts
Of the various groups in an organisation
So as to enable marketing,
engineering, production and services At the most economical levels
Which allow for full customersatisfaction
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Total Quality Management
A philosophy that involves everyone in theorganisation in a continual effort to improvequality and achieve customer satisfaction
With TQM, the whole organisation workstogether to guarantee product quality
The aim is to make products of perfect
quality- with Zero Defect
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Two key philosophies in TQM
A never ending push to improve
( i.e. continuous improvement or Kaizen inJapanese) , and
A goal of customer satisfaction which
involves meeting or exceeding customer
expectation
Total Quality Management
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TQM- Principles
Three important principles
Customer satisfaction
Employee involvement
Continuous improvement in quality
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Deming's 14 points to serve asguidelines for quality management
Create constancy of purpose for continualimprovement of product & service
Adopt the new philosophy for economicstability
Cease dependency on inspection toachieve quality
Deming Philosophy
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End the practice of awarding business on
price tag alone
Improve constantly & for ever the system ofproduction & service
Institute training on the job
Adopt & institute modern methods of
supervision & leadership
Drive out fear
Break down barriers between departments
& individuals
Deming Philosophy
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Eliminate the use of slogans, posters &exhortations
Eliminate work standard & numericalquotas
Remove barriers that rob the hourly workerof the right to pride in workmanship
Institute a vigorous program of education &retraining
Define top managements permanentcommitment to ever-improving quality &
productivity
Deming Philosophy
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Implementation of TQM
Get top management commitment
Find out what the customer wants
Design products with quality in mind Design the process with quality in mind
Build teams of empowered employees
Keep track of results Extend these ideas to suppliers & distributors
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TQM - Failure
Lack of commitment from top management
Focusing on specific techniques rather thanon the system
Not obtaining employee buy-in & participation Program stops with training
Expecting immediate results, not a long termpay-off
Forcing the organisation to adopt methodsthat are not productive or compatible with itsproduction system & personnel
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References
TOTAL QUALITY CONTROL :
ARMAND V. FEIGERBAUM
PRODUCTION AND OPERARTIONS MANAGEMENT
: ASWATHAPPA PRODUCTIVITY TECHNIQUES :
GONDHALEKAR/SALUNKHE
OPERATIONS MANAGEMENT : DONALD WALTERS
TOTAL QUALITY MANAGEMENT :K.SRIDHARA BHAT
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Thank You
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ASSIGNMENT VII-QUALITY
MANAGEMENT Discuss Quality is what the customer wants.
How is this implemented ?
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EVOLUTION OF TQC
Quality Assurance (QA) QA includes QC and also refers to emphasis on the
quality in the design of products, processes and jobs, in
personnel selection and training
Inspection The act of determining conformance or otherwise of the
expected performance
Basis of inspection is usually a specification which is
called inspection standard
Inspection is made by comparing the quality of the
product to its standard
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MEAN CHART
NO. OF SUBGROUPS
LCL
UCL
X
X
X
X
1 2 3 4 K5 6 7 8
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RANGE CHART
NO. OF SUBGROUPS
LCL
UCL
R
R
R
R
1 2 3 4 K5 6 7 8
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npORc CHART
LCL
UCL
PCL= COR
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-R (MEAN-RANGE) CHART FOR VARIABLE CHARACTERISTICS -R CHARTS HAVE TO EXIST AS A PAIR. INTERPRETATION OF
QUALITY OF THE ON-GOING PROCESS HAS TO BE DONE
ANALYSING BOTH THE CHARTS TOGETHER
PROCEDURE
CHOICE OF VARIABLE(X) SELECTION OF RATIONAL SUB-GROUPS
CHOICE OF FREQUENCY
COLLECT K NUMBERS SUB-GROUPS ( USUALLY K=25) EACH OF
COVENIENT SAMPLE SIZE n ( SAY 4-10)
FOR EACH SUB-GROUP, CALCULATE MEAN AND RANGE R
CALCULATE AVERAGE OF THE DIFFERENCE RANGES FOR K
SUB-GROUPS
COMPUTE CENTRAL LINE ( ), UCLR=D4* AND LCLR=D3* , WHERE
D3 AND D4 ARE SAMPLE SIZE DEPENDENT CONSTANTS
X
X
X
RRR
- R CHARTX
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TEST FOR HOMOGENITY
IF SUB-GROUPS NOT HOMOGENOUS, REMOVE OUT OFRANGE LIMIT SAMPLES AND COMPUTE MODIFIED R, UCL
AND LCLR TILL HOMOGENITY IS OBTAINED
FOR HOMOGENOUS SUB-GROUPS( SAY K1), CALCULATE
X=X/K1 , COMPUTE UCLX = X+A2*R AND LCLX=X-A2R,WHERE A2 IS SAMPLE SIZE DEPENDENT CONSTANT TEST FOR HOMOGENITY FOR ALL INDIVIDUAL VALUES O
X FOR K1 SUB-GROUP WITHIN THE VALUES OF UCLX ANDLCLX
IF NON-HOMOGENOUS, REMOVE EXTREMES OUTSIDEUCLXAND LCLX AND RECALCULATE X, UCLX AND LCLX
CONSTRUCT X AND R CHART FOR RATIONAL SUB-GROUPS OBTAINED AFTER TESTING FOR HOMOGENITY
- R CHARTcontdX
MEAN CHART
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CONTROL CHART FOR ATTRIBUTES CONSTRUCTION OF np (NUMBER OF DEFECTIVES CHART) CHART FOR
CONSTANT SAMPLE SIZE n
SAMPLE SIZE=n,
NUMBER OF SUB-GROUPS=K,
NUMBER OF DEFECTIVES PER SUB-GROUP=C
FRACTION DEFECTIVE p=C / n
CALCULATED FOR EACH SUB-GROUP i.e.p1=C1/n, p2=C2/n, .pk=Cn/K
AVERAGE FRACTION DEFECTIVE p=p/K = (p1+p2.pk)/K
OR p= (C1/n+C2/nCK/n)/K
= (C1+C
2..C
K)/(n*K) =C/(n*K)CENTRAL LINE =n*C/(n*K)
UCL= +3 (1-p)
LCL= -3 (1-p) =ZERO, IF NEGATIVE
TEST FOR HOMOGENITY DONE AS IN (X-R) CHART.
pnpnpn
pn pn
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p CHARTS
p CHARTS(FRACTION DEFECTIVE CHART) FOR VARYING SAMPLE SIZE
DATA COLLECTED GIVE SAMPLE SIZE(n1,n2,.nk) FOR K SUB-GROUPS AND VALUES OF NUMBER OF DEFECTIVES(C1,C2,C3..Ck)
FRACTION DEFECTIVES FOR EACH GROUP CALCULATED AS:
p1=C1/n1, p2=C2/n2.pk=Ck/nk
CENTRE LINE p=p/k=(p1+p2.pk)/KUCL FOR EACH SUB-GROUP = p+3p(1-p)]/ SAMPLE SIZE
LCL FOR EACH SUB-GROUP = p-3p(1-p)]/ SAMPLE SIZE=ZERO,IFNEGATIVE
AS SAMPLE SIZE VARIES FOR EACH SUB-GROUP, THERE WILL BE AS MANYVALUES OF LCLs AND UCLs AS THE NUMBER OF VALUES OF SAMPLES ARE (i.e.
n1, n2..nk)
np OR c
CHART
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C CHARTS
C CHARTS( NUMBER OF DEFECTS CHART) FOR
CONSTANT SAMPLE SIZE
SAMPLE SIZE= n
NUMBER OF DEFECTS EXISTING IN ALL THE SAMPLES INEACH SUB-GROUP FOR K SUB-GROUPS ARE SAY C1, C2
.Ck
CENTRE LINE(CL) C=C/K
=(C1+C2+CK)/K
UCL FOR EACH SUB-GROUP=C+3C
LCL FOR EACH SUB-GROUP=C- 3C =0, IF NEGATIVE
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U CHARTS
U CHARTS( NUMBER OF DEFECTS/UNIT) FOR
VARYING SAMPLE SIZE DATA COLLECTED REGARDING SAMPLE SIZE AND NUMBER
OF DEFECTS IN ALL THE SAMPLES FOR EACH OF K SUB-
GROUPS
SAMPLE SIZE n1,n2.nk
NUMBER OF DEFECTS PER SUB-GROUP
=U=C/n=C/SAMPLE SIZE
i.e. U1=C1/n1, U2=C2/n2.Uk=Ck/nk
CENTRE LINE CL=U=U/K=(U1+U2+UK)/K
UCL FOR EACH SUB-GROUP=U+3U/SAMPLE SIZELCL FOR EACH SUB-GROUP=U-3U/SAMPLE SIZE=ZERO, IF
NEGATIVE
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