Quality Control(2)

8/20/2019 Quality Control(2)

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TOTAL QUALITYMANAGEMENT

(Continuous Quality

Improvement)


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QUALITY PLANNING

Who is customer?

What do they need?

QUALITY CONTROL

Ea!uate" com#are" act

QUALITY

I$PRO%E$ENT

Esta&!ish in'rastructure

Who is customer?

What Level of Quality do they need?Are they purchasing to Some Quality Specification?

Any Safety Considerations?

Future Litigation?

Ethical Issues?


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QUALITY PLANNING

Who is customer?

What do they need?

QUALITY CONTROL


QUALITY

I$PRO%E$ENT


QUALITY CONTROL

Inspection

• Destructive• Non-destructive

• Sampling

Process Control

• Monitoring Process (relates to inspection)• Feedbac Control

• Statistical Process Control (no!ing !"en t"e process is

out o# control)

Correction

• $no!ing !"at to correct !"en process is out o# control


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Cost of Quality Before & After

( )( *( +( ,( -( .(

/( 0(

) * + , - . / 0 1 )( )) )* )+ ), )- ). )/ )0 )1 *( *) **

Time 2eries


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Tools for Quality

Control

Check Sheets

areto Charts

Why!Why "iagrams

Cause # Effect "iagrams

Flo$charts

%istograms

Scatter "iagram

Control Charts


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Problem

Solving

Steps

lan

"o

Study

Act

Link these

&$o inQuality

Circle


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CHECK SHEETS

'sed to keep a record

of the num(er and typeof discontinuities over a

specified period of time

or $ithin a certain

(atch of product)

PARETO CHART

A graphical representation ranking

discontinuities from the most to

least significant) 'sed to help

(rainstorm $hat discontinuities* if

$orked upon first* $ould (e the

most likely to produce the greatest

improvement in +uality)

Class E,ample

-ur manufacturing procedure is composed of several steps) Several of these

procedures have lead to discontinuities noticed upon inspection) &he steps causing

defectives are as follo$s.∀ Caulking /01 defectives

∀ Fitting 23 defectives

∀ Connections /45 defectives

∀ &or+ue /1 defectives

∀ 6apping 72 defective

A areto "iagram $ill (e developed)


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W%8!W%8 "IA69A:S

A systematic representation of causes of $hy some occurrence

happens) 'sed to guide (rainstorming sessions)


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FLOW CHARTS

Flo! c"arts are grap"ical representations o# t"e steps involved

in a process% Constructing a #lo! c"art "elps give a betterunderstanding o# t"e systems involved%

Process

Decision3ata

Process

Process

Terminator

Yes

No

Controltransfer


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CAUSE AND EFFECT DIAGRAMS(Fis"bone Diagram)

&sed in brainstorming session to "elp identi#y t"e causes o# 'uality

losses% "is diagram is particularly use#ul a#ter t"e #lo! c"art and

t"e Pareto diagrams "ave been developed%

QUALITY(Effect)Cause

Step /."ecide on the +uality characteristic ;e)g) 9eduction of$o((le during machine rotation<

Step 2.Set up the fish (one (ack(one

Step 5.Identify main factors causing effect ;e)g) Workers*

:aterials* Inspection* &ools<

Step =. Add Cause to each (ranch


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Benefits of Cause and Effect Diagram

• Maing diagram is educational in itsel#

• utline relations"ip

• Note !"at samples need to be taen

• *uide #or discussion

• Causes are actively soug"t and results !ritten on diagram

• +ppropriate data collected - no time !asted

• S"o!s level o# tec"nology


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Problem

Solving

Steps

lan

"o

Study

Act

Link these

&$o inQuality

Circle


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CONTROL CHARTS

• &sed to test i# t"e process is in control

• &sed to see i# signi#icant c"anges "ave occurred in t"e

process over time

“Indiscreet” or

“Continuous Data

Chart” or “X- R Chart”Measurement at time intervals

Measurements compared -

control over time%

,amples.

/engt" (mm) 0olume (cc)

1eig"t (gm) Po!er (!")

ime (sec) Pressure (psi)

0oltage (v)

“Discrete Data Charts” or

“pn-p charts”

Inspection on lot or batc" Note 2 good3de#ective

2 o# parts inspected in t"e lot 4 n

Fraction o# de#ective in lot 4 p

Number o# de#ectives 4 pn


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- R CHART CONSTRUCTION

In t"e manu#acturing process #or t"is eample parts are being

mac"ined !it" a nominal diameter o# 56 mm% Samples are

taen at t"e #ollo!ing times o# day. 7.889 58.889 5:.889 5;.88and


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Step 5. Collect Data

Step e o# t"e subgroup ?in t"is eample = times per day)

4 number o# subgroups ?in t"is eample


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Step =. Find verall Mean ( X )

X 4 X X X X

k

k 5 < 6+ + +%%%

Step 7. Find average value o# range ( R ) R 4 R R R Rk

k 5 < 6+ + +

%%%

Step B. Complete control limits using attac"ed table

For Control C"art

Central /ine - C/ 4 X

&pper Control /imit - &C/ 4 X +


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Step 1.lot Chart


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P CONTROL CHART CONSTRUCTION

An inspector at the end of the manufacturing line for the

production of car $heel rims* at the end of each shift*

inspects the lot of $heel rims made during that shift) -n

good days $hen the $elder is running properly* over =44$heels are made per (atch) -n poor days* as lo$ as 34 to >4

$heels are made per (atch) &he inspector marks on hisher

@check sheet for each (atch the total num(er of $heels

inspected and the num(er of defects returned for re$ork ineach lot)

Class Example


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Step e s"ould be

greater t"an =8 units%

n 4 number in eac" subgroup

pn 4 number o# de#ects in eac" subgroup

Step 6. Compute #raction o# de#ectives (#or E9 multiply by 588)

p = pn/n

Step :. Find t"e +verage Fraction o# De#ectives ( p )

p 4( )

( )

total defectives

total inspected 4

pn

n

∑∑

Step =. Compute t"e Control /imits #or eac" /ot

Central /ine C/ 4 p

&pper Control /imit &C/ 4 p 6 p p

n

( )5−

/o!er Control /imit /CA 4 p - 6 p p

n

( )5−


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Step >."ra$ Control Chart


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PN CONTROL CHART CONSTRUCTION

Class Example

n an assembly line o# !inds"ield !iper motors9 t"e inspector selects

randomly 588 motors per "our to eamine% "e inspector notes on t"e

c"ec s"eetG t"e number o# de#ective motors in eac" 588 selected%

Step 5. Collect Data (lot si>e set constant)


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Step 5. Collect Data (lot si>e set constant)

Step


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QUALITY PLANNING

Who is customer?

What do they need?

QUALITY CONTROL


QUALITY

I$PRO%E$ENT


ISO9000


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Quality Control(2)

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