OM Quality Mgnt_Basics

7/30/2019 OM Quality Mgnt_Basics

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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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