Quality Outline

8/10/2019 Quality Outline

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Quality • CHAPTER FIVE

Chapter

5 Quality

A. Quality: A Management Philosophyq Two competitive priorities that deal with quality High performace desig Cosistet quality

q Firms today must !ridge the gap !etwee cosumer e"pectatios of quality adoperatig capa!ilities [Emphasize that quality is not just a manufacturingissue. Mention The Parkroyal hristchurch! opening "ignette.#

q #uality$ as a essetial competitive priority$ must !e !ased o some operatioaldefiitio

%& Customer'drive defiitios of qualityq #uality has multiple dimesios&q (e or more defiitios of quality may apply&

[Ask the stu$ents for e%amples of &goo$' an$ &poor' quality.#a& Coformace to specificatios)does the product or service meet or e"ceed

advertised levels of performace* [Mention (eagate $isk $ri"es.# !& Value)does the product serve the customers+ purposes cosiderig this price*c& Fitess for use)appearace$ style$ dura!ility$ relia!ility$ craftsmaship$

servicea!ility , how well does the product perform its iteded purpose*d& -upport)eve whe the product performs as e"pected$ if service after the sale is

poor$ the customers+ view of quality dimiishes&

e& Psychological impressios)atmosphere$ image$ or aestheticsf& Factors that ifluece a customer+s perceptio of service o the Iteret.

q /e! pageq Product availa!ilityq 0elivery performaceq Persoal cotact

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1& #uality as a competitive weapo [Mention companies that ha"e use$ quality as a

competiti"e )eapon.#a& Perceptio plays as importat a role$ as does performace& !& Producers that ca match their operatig capa!ilities with cosumer prefereces

have a competitive advatage&c& 3ood quality ca also pay off i higher profits&

q Icreased volumeq Icreased priceq Reduced productio cost

It is importat to ote that whe oe cosiders all of the costs of poor quality$ itactually ca !e less costly to produce a good product tha to produce aiferior oe&

. The osts of Poor Quality q Four ma4or categories of costs are associated with quality maagemet

Prevetio Appraisal Iteral failure E"teral failure

%& PrevetioCosts i this category iclude time$ effort$ ad moey to.a& Redesig the processes to remove causes of defects !& Redesig the product to ma5e it simpler$ easier to producec& Trai employeesd& Trai suppliers

1& Appraisala& Costs icurred to idetify ad assess quality pro!lems

!& Ispectioc& #uality auditsd& -tatistical quality cotrol programs

6& Iteral failureq Costs from defects discovered !efore the product or service is sold

a& 7ield losses)the material costs associated with scrap losses !& Rewor5)time$ space$ ad capacity to store$ reroute to correct defects

8& E"teral failure q Costs whe a defect is discovered after the customer has received the productor servicea& 9oss of mar5et share

!& /arraty servicec& 9itigatiod& Icreased regulatio

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;& /hat are the <hidde= costs of iteral ad e"teral failures*a& >ore la!or !& >ore machie capacityc& Icreased wor5'i'process ivetory

d& E"teded lead timese& Icreased chace of defects reachig the customer f& Icreased pressure to produce more to ma5e up for defectsg& Reduced employee moraleh& >ore defects

*. Employee +n"ol"ementq A 5ey elemet of Total #uality >aagemet

%& Cultural chagea& Top maagemet must motivate cultural chage& !& Everyoe is e"pected to cotri!ute&

c& E"teral customers !uy the product or service&d& Iteral customers are employees i the firm who rely o output of other employees&A assem!ly lie is a chai of iteral customer'supplier relatioships$ with ae"teral customer purchasig the fiished goods&[Mention ,a)aski! Photo -.#

1& Teamsa& 0iffer from more typical <wor5ig group=

q Commo commitmet to overarchig purpose&q -hared leadership roles&q Performace 4udged !y collective efforts&q (pe'eded discussio is valued i meetigs&

q Team mem!ers do real wor5 together rather tha delegate& !& >aagemet+s role i successful teams

q Assig meaigful pro4ects&q Create positive eviromet for meetigs&q Team mem!ers should create clear rules&q -et some immediate performace'orieted tas5s ad goals for early successes&q Cosult people outside the team for ideas$ ispiratio&q Team mem!ers should sped lots of time together&q Have ways other tha direct compesatio to give the team positive

reiforcemet&c& Three approaches to teamwor5

q

Pro!lem'solvig teams ?quality circles@q -pecial'purpose teamsq -elf'maagig teams$ the highest level of wor5er participatio

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. ontinuous +mpro"ement

q Based o the apaese cocept$ kaizenq The philosophy of cotiually see5ig ways to improve operatios&q Dot uique to quality& Applies to process improvemet as well&

%& 3ettig started with cotiuous improvemeta& -PC traiig !& >a5e -PC a ormal aspect of daily operatios&c& Build wor5 teams ad employee ivolvemet&d& tilie pro!lem'solvig techiques withi the wor5 teams&e& 0evelop operator process owership&

1& Pro!lem'solvig process. The 0emig /heela& Pla)select a process eedig improvemet$ documet process$ aalye data$ set

improvemet goals$ discuss alteratives$ assess !eefits ad costs$ develop a plaad improvemet measures&

!& 0o)implemet pla$ moitor improvemets&

c& Chec5)aalye data to evaluate effectiveess of the pla&d& Act)documet ad dissemiate improved process as a stadard procedure&

E. +mpro"ing Quality Through TQM [Mention The TQM /heel. Emphasize its cyclical

nature! i.e.! it ne"er en$s#%& Purchasig cosideratios

a& Buyer must emphasie quality$ delivery$ ad price& !& /or5 with the supplier to o!tai defect'free parts&c& -pecificatios must !e clear ad realistic&d& Allow time to idetify qualified suppliers&e& Improve commuicatio !etwee purchasig$ egieerig$ quality cotrol$ ad

other departmets

1& Product ad service desig a& 0esig chages ca icrease defect rates& !& -ta!le desigs reduce quality pro!lems&c& -ta!le desigs may !ecome o!solete i the mar5etplacese Application -.*: 0elia1ility Analysis 2AP -.*3 for a relia!ility e"ample& The shortaswers are :8&8G for the old car ad 2&;1G for the ew car&

6& Process desig [Mention 4irst 5ational 6ank of hicago.#a& Dew equipmet ca overcome quality pro!lems& !& Cocurret egieerig esures that productio requiremets ad process

capa!ilities are sychroied& [Mention Tera$yne! Photo -..#

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8& #uality fuctio deploymet ?#F0@-i" questios for usig #F0.a& Voice of the customer)/hat do customers eed ad wat* !& Competitive aalysis)Relative to competitors$ how well are we servig

customers*c& Voice of the egieer)/hat techical measures relate to our customers+ eeds*d& Correlatios)/hat are the relatioships !etwee the voice of the customer ad

the voice of the egieer*e& Techical compariso)How does our product or service performace compare to

that of our competitio*f& Trade'offs)/hat are the potetial techical trade'offs*

;& Bechmar5igFour !asic steps of !echmar5ig [Mention competiti"e! functional! internal types.#a& Plaig)idetify process$ leader$ performace measures& !& Aalysis)measure gap$ idetify causes&

c& Itegratio)esta!lish goals ad resource commitmets&d& Actio)develop teams$ implemet pla$ moitor progress$ retur to -tep %&2& Tools for improvig quality

q Die tools for orgaiig ad presetig data [arefully go through the

cause7an$7effect $iagram.#a& Flow diagrams ?Chapter 1@ !& Process charts ?Chapter 1@c& Chec5lists)record the frequecy of occurreced& Histograms)summaries data measured o a cotiuous scalee& Bar charts)!ar height represets the frequecy of occurrecef& Pareto charts)a !ar chart orgaied i decreasig order of frequecyg& -catter diagrams)a plot of two varia!les showig whether they are related

h& Cause'ad'effect$ fish!oe$ or Isha5awa diagrami& 3raphs)a variety of pictorial formats$ such as lie graphs ad pie charts

4. (tatistical Process ontrol 2(P3%& E"amples of Pro!lems 0etected !y -PC[8efine (P an$ relate to other tools in the chapter.#

a& A icrease i the proportio of defective compoets !& A icrease i the average um!er of service complaitsc& A process frequetly fails to coform to desig specificatios

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9. ariation in ;utputsq All sources of variatio ca !e attri!uted to oe of two source categories. commo

causes ad assiga!le causes&%& Commo causes

a& Radom$ or uavoida!le sources of variatio withi a process !& Characteristics of distri!utios

q >ea)the average o!servatioq -pread)the dispersio of o!servatios aroud the meaq -hape)whether the o!servatios are symmetrical or s5ewed

c& Commo cause variatio is ormally distri!uted ?symmetrical@ ad stable ?themea ad spread do ot chage over time@&

1& Assiga!le causesa& Ay cause of variatio that ca !e idetified ad elimiated& !& Change i the mea$ spread$ or shape of a process distri!utio is a symptom that a

assiga!le cause of variatio has developed&

c& After a process is i statistical cotrol$ -PC is used to detect significant change$ idicatig the eed for corrective actio& [Emphasize this point.#6& #uality measuremets

a& Varia!les)a characteristic measured o a cotiuous scaleq Advatage. if defective$ we 5ow !y how much)the directio ad magitude

of correctios are idicated&q 0isadvatage. precise measuremets are required&

!& Attri!utes)a characteristic couted i discrete uits$ ?yes'o$ iteger um!er@q sed to determie coformace to comple" specificatios$ or whe measurig

varia!les is too costlyq Advatages. #uic5ly reveals whe quality has chaged$ provides a iteger um!er of

how many are defective Requires less effort ad fewer resources tha measurig varia!les

q 0isadvatages. 0oes+t show !y how much they were defective$ the directio ad

magitude of correctios are ot idicated Requires more o!servatios$ as each o!servatio provides little iformatio

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8& -ampliga& Complete ispectio

q sed whe Costs of failure are high relative to costs of ispectio

Ispectio is automated !& -amplig plas

q sed whe Ispectio costs are high Ispectio destroys the product

q -ome defectives lots may !e purchased ad some good lots may !e re4ectedwhe The sample does ot perfectly represet the populatio Testig methods are imperfect

q -amplig plas iclude -ample sie$ n radom o!servatios

Time !etwee successive samples 0ecisio rules that determie whe actio should !e ta5ec& -amplig distri!utios

q -ample meas are usually dispersed a!out the populatio mea accordig tothe ormal pro!a!ility distri!utio ?referece the cetral limit theoremdescri!ed i statistics te"ts@& [+t is important to $istinguish 1et)een the$istri1ution of sample means an$ the process $istri1ution itself.#

;& Cotrol chartsa& sed to 4udge whether actio is required !& A sample characteristic measured a!ove the upper cotrol limit ?UCL@ or

!elow the lower cotrol limit ? LCL@ idicates that a assiga!le cause pro!a!ly e"ists& [6e sure that the stu$ent un$erstan$s that the UCL

an$ LCL are not pro$uct or ser"ice specifications.#c& -teps for usig a cotrol chart.

q Ta5e a radom sample$ measure the quality characteristic$ ad calculate avaria!le of attri!ute measure&

q Plot the statisticJ if it falls outside the cotrol limits$ loo5 for assiga!le causes&q Elimiate the cause if it degrades quality& Icorporate the cause if it improves

quality& Recalculate the cotrol chart&q Periodically repeat the procedure&

d& Idicators of out of cotrol coditiosq A tred i the o!servatios ?the process is driftig@q A sudde or step chage i the o!servatios

q A ru of five or more o!servatios o the same side of the mea ?If we flip acoi ad get <heads= five times i a row$ we !ecome suspicious of the coi or of the coi flippig process&@

q -everal o!servatios ear the cotrol limits ?Dormally oly % i 1o!servatios are more tha 1 stadard deviatios from the mea&@

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<. (tatistical Process ontrol Metho$sq >easure curret quality&q 0etect whether the process has chaged&

%& Cotrol charts for varia!lesq #uality characteristics iclude varia!les$ which are measured over a cotiuum&

a& Rage charts

q >oitor process varia!ility First remove assiga!le causes of variatio& /hile process is i cotrol$ collect data to estimate the average rage of

output that occurs&

To esta!lish the upper ad lower cotrol limits for the R'chart$ we use Ta!le :&%$

which provides two factorsJ D6 ad D8 & These factors esta!lish the UCL R ad

LCL R at three stadard deviatios a!ove ad !elow R &

UCL R = D4 R

LCL R = D3 R

!& x ' charts

q The process average is plotted o the x ' chart after the process varia!ility is icotrol&

q The upper ad lower cotrol limits ca !e esta!lished i two ways& If the stadard deviatio of the process distri!utio is 5ow$ we could

place UCL ad LCL at < z = stadard deviatios away from the mea$depedig o the desired cofidece iterval&

UCL x z

LCL x z

x x

x x

= +

= −

σ

σ

where

σ σ

x

n=

(r we could use Ta!le ;&% to fid A1$ which whe multiplied !y the

previously determied R $ places UCL ad LCL three stadard deviatiosa!ove ad !elow the mea&

UCL x A R

LCL x A R

x

x

= +

= −

1

1

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c& sig x ' ad R'charts to moitor a processq Costruct the R'chart&q Compute the rage for each sample&q Plot the rages o the R'chart&

q Costruct x 'chart&q Compute the mea for each sample&q Plot the sample meas o the x 'chart&q se Application -.: ontrol harts for aria1les 2AP -.3 to

demostrate the costructio of R' ad x'!ar charts& Because the rage isout of cotrol$ the x'!ar calculatio is moot& Cosider droppig sample 2 !ecause of a ioperative scale& The resultig cotrol charts idicate thatthe process is actually i cotrol&

1& Cotrol charts for attri!utes [Mention e%amples from 1anking an$ manufacturing.Emphasize that $efects can 1e counte$.#a& p'chart)populatio proportio defective

q

Ta5e a radom sample of n uits&q Cout the um!er of defectives&q Proportio defective K um!er of defectives L sample sieq Plot sample proportio defective o a chart& If it is outside the rage !etwee

the upper ad lower cotrol limits$ search for a assiga!le cause& If cause isfoud do ot use these data to determie the cotrol limits&

UCL p z

LCL p z

p p

p p

= +

= −

σ

σ

where

σ

p

p p

n=

−( )%

q Two thigs to ote. The lower cotrol limit caot !e egative& /he the um!er of defects is less tha the LCL$ the the system is out of

cotrol i a good way& /e wat to fid the assiga!le cause& Fid what wasuique a!out this evet that caused thigs to wor5 out so well&

q se Application -.=: p7hart for Attri1utes 2AP -.=3 for a e"ample of a p'

chart pro!lem& The short aswers are. p = 1;& J UCL p = I I28& J LCL p = J

I C!"R!L

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!& c'chart)more tha oe defect per uitq Ta5e a radom sample of oe&q Ispect the quality attri!ute&q Cout the um!er of defects&

UCL c z

LCL c z

c c

c c

= +

= −

σ

σ

where

σ c c=

q Plot the um!er of defectives o a chart& If it is outside the rage !etwee theupper ad lower cotrol limits$ search for the assiga!le cause& If cause isfoud$ do ot use these data to determie the cotrol limits&

c& The Poisso distri!utio mea ad stadard deviatio are !oth descri!ed usig thesame um!er$ c & The mea equals c $ ad the stadard deviatio equals c &

d& /e set upper ad lower cotrol limits i a maer similar to p'charts&e& se Application -.>: c7hart for Attri1utes 2AP -.>3 for a e"ample of a c'

chart&

+. Process apa1ilityq Cotrol limits are !ased o the mea ad varia!ility of the sampling

#istribution$ ot the desig specificatios& [This is an important point that is$ifficult for the stu$ents.#

%& 0efiig process capa!ilityA process is capa!le wheq The specified tolerace width is greater tha rage of actual process outputs

an# q The process is cetered ear the omial or target valuea& Process capa!ility ratio

q Compares the tolerace width ?upper spec M lower spec@ to the rage of actual process outputs& The portio of a distri!utio withi N 6 σ of the mea williclude the vast ma4ority ?&:8G@ of the actual process outputs&

q The process is capa!le whe the ratio

C p =Upper specification – Lower specification

6σ

≥ 1.00

qProcess capa!ility ratios greater tha oe ?say %&66@ allow for some shift i the process distri!utio !efore !ad output is geerated&

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!& Process capa!ility ide"q Idicates whether the process is sufficietly cetered !y measurig the distace

!etwee the process ceter ad the specificatio limits ad the comparig thatto 6σ &

q The process capa!ility ide" is

C x x

pk =

− −

NMM

>iimum of9ower specificatio

6

Epper specificatio

6σ σ

$

q If the process capa!ility ide" is less tha oe$ the process ceter is too close tooe of the specificatio limits ad will geerate too may defects&

1& 0etermiig the capa!ility of a process usig cotiuous improvemet-tep %& Collect data$ calculate mea ad stadard deviatio for the process&-tep 1& Costruct the process cotrol charts&-tep 6& Compare the radom samples to the cotrol limits& Elimiate the assiga!le

causes ad recalculate the cotrol limits as appropriate util 1 cosecutiveradom samples fall withi the cotrol limits& This idicates that the process isi statistical cotrol&

-tep 8& Calculate the process capa!ility ratio ad the process capa!ility ide"& If the process is capa!le$ documet chages to the process ad moitor the outputusig cotrol charts& If it is ot capa!le$ elimiate the causes of variatio adrecalculate the cotrol limits& Retur to step 6&

se Application -.-: Process apa1ility Analysis 2AP -.-3 to !rig together thecocepts of statistical cotrol ad process cotrol&

6& #uality egieerigq A approach com!iig egieerig ad statistical methods to optimize product desig ad maufacturig processes

q Before Taguchi$ maagers assumed the goal was to produce products falligaywhere !etwee their desig toleraces&q #uality loss fuctio is optimum ?ero@ whe the product+s quality measure ise"actly o the target value&q Cotiually search for places ways to reduce all varia!ility

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?. +nternational Quality 8ocumentation (tan$ar$s%& /hat is I-( *

a& Certified compaies are listed i a directory& !& Compliace with I-( stadards idicates quality claims ca !e documeted&

1& I-( %8)a evirometal maagemet systema& -tadards require that compaies 5eep trac5 of their raw materials use ad the

geeratio$ treatmet$ ad disposal of haardous wastes& !& Compaies must prepare a pla for ogoig improvemet i evirometal

performace&c& -tadards cover the followig areas.

q Evirometal maagemet systemq Evirometal performace evaluatioq Evirometal la!eligq 9ife cycle assessmets

6& Beefits of I-( Certificatio

a& E"teral)potetial sales advatage !& Iteral)provides guidace i startig the T#> 4ourey

,. Malcolm 6al$rige 5ational Quality A)ar$

[Mention )ell7kno)n companies )ho ha"e recei"e$ the a)ar$.#%& Esta!lished i %:1& Damed for -ecretary of Commerce >alcolm Baldrige6& Improved quality as a meas of reducig the trade deficit8& 9ear stregths ad wea5esses ad fid ways to improve operatios;& -eve criteria

a& 9eadership !& -trategic plaig

c& Customer ad mar5et focusd& Iformatio aalysise& Huma resource focusf& Process maagemetg& Busiess results

@. TQM Across the ;rganizationq 0iscuss >errill 9ych Credit Corporatio >alcolm Baldrige wier Commuicatio from top to !ottom i the orgaiatio Employees are empowered to ta5e iitiative ad resposi!ility

<Voice of the cliet= approach

6:

Quality Outline

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