Quality Management

N.K.Agarwal

Quality Management

• Product and service quality can be defined as – 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

Quality features of a Product

• Product features– Performance– Reliability– Durability– Ease of use– Serviceability

Quality features of a Product

– Esthetics– Availability of options and expandability– Reputation

• Freedom from deficiencies– Free of defects and errors at delivery,

during use and during servicing– Sales, billing and other business processes

free of errors

Quality features of Service

• Quality of a service judged by– Reliability– Availability– Credibility– Security– Competence of staff– Understanding of customer needs– Responsiveness to customers

– Courtesy of staff– Comfort of surroundings– Communication between participants– Associated goods provided with the service

• Freedom from deficiencies– Service free of errors during original and

future service transactions– Sales, billing and other business processes

free of errors

Quality features of Service

Quality Control (Q.C.)

• Procedures for meeting the goals• Generally 4 steps

– Setting standards– Appraising conformance– Acting when necessary– Planning for improvement

Statistical Quality Control (SQC)

• Application of the statistical techniques to accept or reject products already produced or to control the process, and therefore product quality while the part is being made.– Former is named as acceptance sampling– The later process called process control

• These are two prominent techniques of QC

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 through control charts

• First developed by Dr. Walter A. Shewart of Bell Telephone Labs during 1930s

• Horizontal extensions of the bell shaped curve

Bell Shaped Curve

SIZE

NO

. O

F C

AS

ES

Control Chart

TIME

QU

ALI

TY

VA

RI A

TIO

N

LCL

CL AVERAGE QUALITY

UCL

Control Charts

• Types– Control charts for variables– Control charts for attributes

• Variables– Quality characteristics that can be measured

on a continuous 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

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

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 control or 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

• -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

• TEST FOR HOMOGENITY• IF SUB-GROUPS NOT HOMOGENOUS, REMOVE OUT OF

RANGE LIMIT SAMPLES AND COMPUTE MODIFIED R, UCLR 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 OF X FOR K1 SUB-GROUP WITHIN THE VALUES OF UCLX AND LCLX

• IF NON-HOMOGENOUS, REMOVE EXTREMES OUTSIDE

UCLX AND LCLX AND RECALCULATE X, UCLX AND LCLX

• CONSTRUCT X AND R CHART FOR RATIONAL SUB-GROUPS OBTAINED AFTER TESTING FOR HOMOGENITY

- R CHART…contdX

MEAN CHART

MEAN CHART

NO. OF SUBGROUPS

SA

MP

LE M

EA

N

LCL

UCL

X

X

X

X

X

1 2 3 4 K5 6 7 8

RANGE CHART

NO. OF SUBGROUPS

SA

MP

LE R

AN

GE

LCL

UCL

R

R

R

R

R

1 2 3 4 K5 6 7 8

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 equal chance of being selected and permit logical inferences to be made about the lot quality based on sample evidence

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

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 as intended: Producer’s risk ()

• Type-II error– An error when sample leads to conclusion

that the process is satisfactory , when in fact, the process is not working as intended: Consumer’s risk ()

Total Quality Management

• A philosophy that involves everyone in the organisation in a continual effort to improve quality and achieve customer satisfaction

• With TQM, the whole organisation works together to guarantee product quality

• The aim is to make products of perfect quality- with Zero Defect

TQM- Principles

• Three important principles– Customer satisfaction– Employee involvement– Continuous improvement in quality

• Deming's 14 points to serve as guidelines for quality management– Create constancy of purpose for continual

improvement of product & service– Adopt the new philosophy for economic

stability– Cease dependency on inspection to

achieve quality

Deming Philosophy

– End the practice of awarding business on price tag alone

– Improve constantly & for ever the system of production & service

– Institute training on the job– Adopt & institute modern methods of

supervision & leadership– Drive out fear– Break down barriers between departments

& individuals

Deming Philosophy

– Eliminate the use of slogans, posters & exhortations

– Eliminate work standard & numerical quotas

– Remove barriers that rob the hourly worker of the right to pride in workmanship

– Institute a vigorous program of education & retraining

– Define top management’s permanent commitment to ever-improving quality & productivity

Deming Philosophy

Quality Management

• Quality of a Product or Service must meet or exceed the customers expectation Quality in the organisation has to be built into the organisation in stages

• Statistical Quality Control can be applied to the products under processing as well as manufactured lots in large quantities

• Total Quality Management aims at – Customer satisfaction– Employees involvement, and – Continuous improvement in quality

Thank You

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

ASSIGNMENT VII-QUALITY MANAGEMENT

• Discuss “Quality is what the customer wants”. How is this implemented ?

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 customer satisfaction

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

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/n……CK/n)/K

= (C1+C2……..CK)/(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.

pnpn

pn

pn pn

np OR c CHARTnp

OR

c

LCL

UCL

PCL= COR

‘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)/K

UCL FOR EACH SUB-GROUP = p+3p(1-p)]/ SAMPLE SIZE

LCL FOR EACH SUB-GROUP = p-3p(1-p)]/ SAMPLE SIZE=ZERO,IF NEGATIVE

– AS SAMPLE SIZE VARIES FOR EACH SUB-GROUP, THERE WILL BE AS MANY VALUES OF LCLs AND UCLs AS THE NUMBER OF VALUES OF SAMPLES ARE (i.e. n1, n2……..nk)

np OR c CHART

‘ C ‘ CHARTS

• ‘ C ‘ CHARTS( NUMBER OF DEFECTS CHART) FOR CONSTANT SAMPLE SIZESAMPLE SIZE= n

NUMBER OF DEFECTS EXISTING IN ALL THE SAMPLES IN EACH 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

‘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 SIZE

LCL FOR EACH SUB-GROUP=U-3U/SAMPLE SIZE=ZERO, IF NEGATIVE

• Two key philosophies in TQM– A never ending push to improve ( i.e.

continuous improvement or Kaizen in Japanese) , and

– A goal of customer satisfaction which involves meeting or exceeding customer expectation

Total Quality Management

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

TQM - Failure

• Lack of commitment from top management• Focusing on specific techniques rather than

on the system• Not obtaining employee buy-in & participation• Program stops with training• Expecting immediate results, not a long term

pay-off• Forcing the organisation to adopt methods

that are not productive or compatible with its production system & personnel