Process Performance and Quality - Faculty of Engineering ...adfisher/7943-05/Chpt5/ch05.pdf · Process Performance and Quality ... To Accompany Krajewski & Ritzman Operations Management:

To Accompany Krajewski & Ritzman Operations Management: Strategy and Analysis, Seventh Edition © 2004 Prentice Hall, Inc. All rights reserved.

Process Performance Process Performance and Qualityand Quality

Chapter 5Chapter 5


Implementchanges

6Redesignprocess

5

Evaluating Process Evaluating Process PerformancePerformance

Documentprocess

3

Definescope

2

Evaluateperformance

4

Figure 5.1Figure 5.1

Identify opportunity

1


The Costs of The Costs of Poor QualityPoor Quality

•• Prevention CostsPrevention Costs•• Appraisal CostsAppraisal Costs•• Internal Failure CostsInternal Failure Costs•• External Failure CostsExternal Failure Costs


Customer Customer satisfactionsatisfaction

TQMTQMWheelWheel



CustomerCustomer--DrivenDrivenDefinitions of QualityDefinitions of Quality•• Conformance to SpecificationsConformance to Specifications•• ValueValue•• Fitness for UseFitness for Use•• SupportSupport•• Psychological ImpressionsPsychological Impressions


EmployeeEmployeeInvolvementInvolvement

•• Cultural Cultural ChangeChange

•• TeamsTeams


PlanPlan

DoDo

CheckCheck

ActAct

DemingDemingWheelWheel



Statistical Process ControlStatistical Process Control•• SPC: The application of statistical techniques to SPC: The application of statistical techniques to

determine whether a process is delivering what a determine whether a process is delivering what a customer wantscustomer wants

•• Evaluating the performance of processes requires a Evaluating the performance of processes requires a variety of data gathering approaches.variety of data gathering approaches.

•• Variation of outputs Variation of outputs –– Common causesCommon causes

•• Random, or unavoidable sources of variation within a processRandom, or unavoidable sources of variation within a process•• Characteristics of distributionsCharacteristics of distributions

»» MeanMean——the average observationthe average observation»» SpreadSpread——the dispersion of observations around the the dispersion of observations around the

meanmean»» ShapeShape——whether the observations are symmetrical or whether the observations are symmetrical or

skewedskewed•• Common cause variation is normally distributed (symmetrical) Common cause variation is normally distributed (symmetrical)

and stable (the mean and spread do not change over time).and stable (the mean and spread do not change over time).


Common CausesCommon Causes

x =xi

i =1

n

∑n

σ =xi − x ( )∑ 2

n−1

Mean Standard Deviation/ Spread


Statistical Process ControlStatistical Process Control•• Variation of outputs Variation of outputs

–– Assignable causesAssignable causes•• Any cause of variation that can be identified and Any cause of variation that can be identified and

eliminated.eliminated.•• Change in the mean, spread, or shape of a process Change in the mean, spread, or shape of a process

distribution is a symptom that an assignable cause of distribution is a symptom that an assignable cause of variation has developed.variation has developed.

•• After a process is in statistical control, SPC is used to After a process is in statistical control, SPC is used to detect significant change, indicating the need for detect significant change, indicating the need for corrective action. spread do not change over time).corrective action. spread do not change over time).


Assignable CausesAssignable Causes

(a) Location(a) LocationGramsGrams

AverageAverage


AverageAverage



(b) Spread(b) Spread GramsGrams

AverageAverage




(c) Shape(c) Shape GramsGrams

AverageAverage



Statistical Process ControlStatistical Process Control•• Performance measurements Performance measurements

–– Variables Variables —— service or product characteristics measured on service or product characteristics measured on a continuous scalea continuous scale

•• Advantage: if defective, we know by how much Advantage: if defective, we know by how much —— the direction the direction and magnitude of corrections are indicated.and magnitude of corrections are indicated.

•• Disadvantage: precise measurements are required.Disadvantage: precise measurements are required.–– Attributes Attributes —— a characteristic counted in discrete units, (yesa characteristic counted in discrete units, (yes--

no, integer number)no, integer number)•• Used to determine conformance to complex specifications, or Used to determine conformance to complex specifications, or

when measuring variables is too costlywhen measuring variables is too costly•• Advantages: Advantages:

–– Quickly reveals when quality has changed, provides an integer Quickly reveals when quality has changed, provides an integer number of how many are defectivenumber of how many are defective

–– Requires less effort, and fewer resources than measuring variablRequires less effort, and fewer resources than measuring variableses•• Disadvantages: Disadvantages:

–– Doesn't show by how much they were defective, the direction and Doesn't show by how much they were defective, the direction and magnitude of corrections are not indicatedmagnitude of corrections are not indicated

–– Requires more observations, since each observation provides littRequires more observations, since each observation provides little le informationinformation


Statistical Process ControlStatistical Process Control•• SamplingSampling

–– Complete inspectionComplete inspection•• Used whenUsed when

–– Costs of failure are high relative to costs of inspectionCosts of failure are high relative to costs of inspection–– Inspection is automatedInspection is automated

–– Sampling plansSampling plans•• Used when Used when

–– Inspection costs are highInspection costs are high–– Inspection destroys the productInspection destroys the product

•• Sampling plans includeSampling plans include–– Sample size, n random observationsSample size, n random observations–– Time between successive samplesTime between successive samples–– Decision rules that determine when action should be takenDecision rules that determine when action should be taken

•• Sampling distributionsSampling distributions–– Sample means are usually dispersed about the population mean Sample means are usually dispersed about the population mean

according to the normal probability distribution (reference the according to the normal probability distribution (reference the central limit theorem described in statistics texts).central limit theorem described in statistics texts).


Sample Means and theSample Means and theProcess DistributionProcess Distribution


MeanMean

ProcessProcessdistributiondistribution

TimeTime

Distribution ofDistribution ofsample meanssample means


Statistical Process ControlStatistical Process Control•• Control chartsControl charts

–– Used to judge whether action is requiredUsed to judge whether action is required–– A sample characteristic measured above the upper A sample characteristic measured above the upper

control limit (UCL) or below the lower control limit control limit (UCL) or below the lower control limit (LCL) indicates that an assignable cause probably (LCL) indicates that an assignable cause probably exists.exists.

–– Steps for using a control chart:Steps for using a control chart:•• Take a random sample, measure the quality Take a random sample, measure the quality

characteristic, and calculate a variable or attribute characteristic, and calculate a variable or attribute performance measure.performance measure.

•• Plot the statistic; if it falls outside the control limits, lookPlot the statistic; if it falls outside the control limits, lookfor assignable causes.for assignable causes.

•• Eliminate the cause if it degrades performance. Eliminate the cause if it degrades performance. Incorporate the cause if it improves performance. Incorporate the cause if it improves performance. Recalculate the control chart.Recalculate the control chart.

•• Periodically repeat the procedure.Periodically repeat the procedure.


Statistical Process ControlStatistical Process Control•• Control chartsControl charts

–– Indicators of out of control conditionsIndicators of out of control conditions•• A trend in the observations (the process is drifting)A trend in the observations (the process is drifting)•• A sudden or step change in the observationsA sudden or step change in the observations•• A run of five or more observations on the same side of A run of five or more observations on the same side of

the mean (If we flip a coin and get the mean (If we flip a coin and get ““headsheads”” five times in a five times in a row, we become suspicious of the coin or of the coin row, we become suspicious of the coin or of the coin flipping process.)flipping process.)

•• Several observations near the control limits (Normally Several observations near the control limits (Normally only 1 in 20 observations are more than 2 standard only 1 in 20 observations are more than 2 standard deviations from the mean.) deviations from the mean.)


Control ChartsControl Charts

UCLUCL

NominalNominal

LCLLCL

SamplesSamplesFigure 5.6Figure 5.6

Assignable Assignable causes likelycauses likely

11 22 33


Using Control Charts for Using Control Charts for Process ImprovementProcess Improvement

•• Sample the processSample the process•• When changes are indicated, When changes are indicated,

find the assignable causefind the assignable cause•• Eliminate problems, incorporate Eliminate problems, incorporate

improvementsimprovements•• Repeat the procedureRepeat the procedure


Control Chart ExamplesControl Chart Examples

NominalNominal

UCLUCL

LCLLCL

Sample numberSample number

Varia

tions

Varia

tions

Figure 5.7 (a)Figure 5.7 (a)



NominalNominal

UCLUCL

LCLLCL


Varia

tions

Varia

tions

Figure 5.7 (b)Figure 5.7 (b)



NominalNominal

UCLUCL

LCLLCL


Varia

tions

Varia

tions

Figure 5.7 (c)Figure 5.7 (c)



NominalNominal

UCLUCL

LCLLCL


Varia

tions

Varia

tions

Figure 5.7 (d)Figure 5.7 (d)



NominalNominal

UCLUCL

LCLLCL


Varia

tions

Varia

tions

Figure 5.7 (e)Figure 5.7 (e)


Statistical Process ControlStatistical Process Control•• Control charts for variablesControl charts for variables

–– Process performance characteristics include Process performance characteristics include variables, which are measured over a continuum.variables, which are measured over a continuum.

–– Range chartsRange charts•• Monitor process variabilityMonitor process variability

–– First remove assignable causes of variation.First remove assignable causes of variation.–– While process is in control, collect data to estimate While process is in control, collect data to estimate

the average range of output that occurs.the average range of output that occurs.–– To establish the upper and lower control limits for To establish the upper and lower control limits for

the Rthe R--chart, we use Table 5.1, which provides two chart, we use Table 5.1, which provides two factors; D3 and D4. These factors establish the factors; D3 and D4. These factors establish the UCLR and LCLR at three standard deviations above UCLR and LCLR at three standard deviations above and below . and below .

UCLR = D4 R

LCLR = D3 R


Control ChartsControl Chartsfor Variablesfor Variables

West Allis IndustriesWest Allis Industries



Example 5.1Example 5.1

Sample SampleNumber 1 2 3 4 R x

1 0.5014 0.5022 0.5009 0.50272 0.5021 0.5041 0.5024 0.50203 0.5018 0.5026 0.5035 0.50234 0.5008 0.5034 0.5024 0.50155 0.5041 0.5056 0.5034 0.5039

Special Metal Screw

_





1 0.5014 0.5022 0.5009 0.5027 0.0018 0.50182 0.5021 0.5041 0.5024 0.50203 0.5018 0.5026 0.5035 0.50234 0.5008 0.5034 0.5024 0.50155 0.5041 0.5056 0.5034 0.5039

Special Metal Screw

_

0.5027 0.5027 –– 0.50090.5009 == 0.00180.0018





1 0.5014 0.5022 0.5009 0.5027 0.0018 0.50182 0.5021 0.5041 0.5024 0.50203 0.5018 0.5026 0.5035 0.50234 0.5008 0.5034 0.5024 0.50155 0.5041 0.5056 0.5034 0.5039

Special Metal Screw

_

(0.5014 + 0.5022 +(0.5014 + 0.5022 +0.5009 + 0.5027)/40.5009 + 0.5027)/4 == 0.50180.5018

0.5027 0.5027 –– 0.50090.5009 == 0.00180.0018




1 0.5014 0.5022 0.5009 0.5027 0.0018 0.50182 0.5021 0.5041 0.5024 0.5020 0.0021 0.50273 0.5018 0.5026 0.5035 0.5023 0.0017 0.50264 0.5008 0.5034 0.5024 0.5015 0.0026 0.50205 0.5041 0.5056 0.5034 0.5047 0.0022 0.5045

R = 0.0021x = 0.5027

Special Metal Screw


=

_




Control Charts – Special Metal ScrewR-Charts R = 0.0021

UCLR = D4RLCLR = D3R



Control ChartsControl Chartsfor Variablesfor VariablesTable 5.1 Control Chart FactorsTable 5.1 Control Chart Factors

Factor for UCLFactor for UCL Factor forFactor for FactorFactorSize ofSize of and LCL forand LCL for LCL forLCL for UCL forUCL forSampleSample xx--ChartsCharts RR--ChartsCharts RR--ChartsCharts

((nn)) ((AA22)) ((DD33)) ((DD44))

22 1.8801.880 00 3.2673.26733 1.0231.023 00 2.5752.57544 0.7290.729 00 2.2822.28255 0.5770.577 00 2.1152.11566 0.4830.483 00 2.0042.00477 0.4190.419 0.0760.076 1.9241.92488 0.3730.373 0.1360.136 1.8641.86499 0.3370.337 0.1840.184 1.8161.816

1010 0.3080.308 0.2230.223 1.7771.777




Control Charts—Special Metal ScrewR-Charts R = 0.0021 D4 = 2.282

D3 = 0UCLR = D4RLCLR = D3R





D3 = 0

UCLR = 2.282 (0.0021) = 0.00479 in.






D3 = 0

UCLR = 2.282 (0.0021) = 0.00479 in.LCLR = 0 (0.0021) = 0 in.






D3 = 0

UCLR = 2.282 (0.0021) = 0.00479 in.LCLR = 0 (0.0021) = 0 in.



Range Chart Range Chart --Special Metal ScrewSpecial Metal Screw





Control Charts—Special Metal ScrewX-Charts

UCLx = x + A2RLCLx = x - A2R

==

R = 0.0021x = 0.5027=




Control Charts—Special Metal ScrewX-Charts


==

R = 0.0021x = 0.5027=

Table 5.1 Control Chart FactorsTable 5.1 Control Chart Factors

Factor for UCLFactor for UCL Factor forFactor for FactorFactorSize ofSize of and LCL forand LCL for LCL forLCL for UCL forUCL forSampleSample xx--ChartsCharts RR--ChartsCharts RR--ChartsCharts

((nn)) ((AA22)) ((DD33)) ((DD44))

22 1.8801.880 00 3.2673.26733 1.0231.023 00 2.5752.57544 0.7290.729 00 2.2822.28255 0.5770.577 00 2.1152.11566 0.4830.483 00 2.0042.00477 0.4190.419 0.0760.076 1.9241.92488 0.3730.373 0.1360.136 1.8641.86499 0.3370.337 0.1840.184 1.8161.816

1010 0.3080.308 0.2230.223 1.7771.777




Control Charts—Special Metal Screwx-Charts


==

R = 0.0021 A2 = 0.729x = 0.5027=





UCLx = 0.5027 + 0.729 (0.0021) = 0.5042 in.


==

R = 0.0021 A2 = 0.729x = 0.5027=





UCLx = 0.5027 + 0.729 (0.0021) = 0.5042 in.LCLx = 0.5027 – 0.729 (0.0021) = 0.5012 in.


==

R = 0.0021 A2 = 0.729x = 0.5027=


xx--ChartChart——Special Metal ScrewSpecial Metal Screw



xx--ChartChart——Special Metal ScrewSpecial Metal Screw


• Sample the process• Find the assignable cause• Eliminate the problem• Repeat the cycle


Control ChartsControl Chartsfor Variables Using for Variables Using σσ

UCLUCLxx = 5.0 + 1.96(1.5)/ 6 = 6.20 min= 5.0 + 1.96(1.5)/ 6 = 6.20 min

UCLUCLxx = 5.0 = 5.0 –– 1.96(1.5)/ 6 = 3.80 min1.96(1.5)/ 6 = 3.80 minExample 5.2Example 5.2

UCLUCLxx = = xx + + zzσσxx

LCLLCLxx = = xx –– zzσσxx

σσxx = = σσ// nn

====

Sunny Dale BankSunny Dale Bank

xx == 5.0 minutes5.0 minutesσσ == 1.5 minutes1.5 minutesnn == 6 customers6 customerszz == 1.961.96

==


Control ChartsControl Chartsfor Attributesfor Attributes

HOMETOWN BANK

Hometown BankHometown Bank


Control ChartsControl Chartsfor Attributesfor AttributesHometown BankHometown Bank

UCLUCLpp = = pp + + zzσσpp

LCLLCLpp = = pp –– zzσσpp

σσpp = = pp(1 (1 –– pp))//nnExample 5.3Example 5.3





LCLLCLpp = = pp -- zzσσpp

σσpp = = pp(1 (1 -- pp))//nn

Sample WrongNumber Account Number

1 152 123 194 25 196 47 248 79 10

10 1711 1512 3

Total 147

Total defectivesTotal observationsp =

n = 2500






σσpp = = pp(1 (1 -- pp))//nn


1 152 123 194 25 196 47 248 79 10

10 1711 1512 3

Total 147

14712(2500)

p =

n = 2500






σσpp = = pp(1 (1 -- pp))//nn


1 152 123 194 25 196 47 248 79 10

10 1711 1512 3

Total 147

p = 0.0049

n = 2500






σσpp = = pp(1 (1 -- pp))//nn

Sample Wrong ProportionNumber Account Number Defective

1 15 0.0062 12 0.00483 19 0.00764 2 0.00085 19 0.00766 4 0.00167 24 0.00968 7 0.00289 10 0.004

10 17 0.006811 15 0.00612 3 0.0012

Total 147

p = 0.0049

n = 2500





σσpp = = pp(1 (1 –– pp))//nn

n n = 2500 = 2500 pp = 0.0049= 0.0049






σσpp = 0.0049(1 = 0.0049(1 –– 0.0049)/25000.0049)/2500

n n = 2500 = 2500 pp = 0.0049= 0.0049






σσpp = 0.0014= 0.0014

n n = 2500 = 2500 pp = 0.0049= 0.0049




σσpp = 0.0014= 0.0014

n n = 2500 = 2500 pp = 0.0049= 0.0049


UCLUCLpp = 0.0049 + 3(0.0014)= 0.0049 + 3(0.0014)

LCLLCLpp = 0.0049 = 0.0049 –– 3(0.0014)3(0.0014)


UCLUCLpp = 0.0091= 0.0091

LCLLCLpp = 0.0007= 0.0007


σσpp = 0.0014= 0.0014

n n = 2500 = 2500 pp = 0.0049= 0.0049



p-ChartWrong Account Numbers



p-ChartWrong Account Numbers


• Sample the process• Find the assignable cause• Eliminate the problem• Repeat the cycle



WoodlandWoodlandPaper Paper CompanyCompany



cc = 20 = 20 z z = 2= 2

UCLUCLcc = = cc + + z cz c

LCLLCLcc = = cc –– z cz cExample 5.4Example 5.4

WoodlandWoodlandPaperPaperCompanyCompany




cc = 20 = 20 z z = 2= 2

UCLUCLcc = 20 + 2 20= 20 + 2 20

LCLLCLcc = 20 = 20 –– 2 202 20





cc = 20 = 20 z z = 2= 2

UCLUCLcc = 28.94= 28.94

LCLLCLcc = 11.06= 11.06










• Sample the process• Find the assignable cause• Incorporate the improvement• Repeat the cycle


Six Sigma Six Sigma ImplementationImplementation

•• Top Down CommitmentTop Down Commitment•• Measurement Systems to Track Measurement Systems to Track

ProgressProgress•• Tough Goal SettingTough Goal Setting•• EducationEducation•• CommunicationCommunication•• Customer PrioritiesCustomer Priorities

ASQ 6 Sigma ForumASQ 6 Sigma Forum


ISOISO90009000

ISOISO1400014000

International Quality International Quality DocumentationDocumentation

•• Environmental Management Environmental Management SystemsSystems

•• Environmental Performance Environmental Performance EvaluationEvaluation

•• Environmental LabelingEnvironmental Labeling•• LifeLife--Cycle AssessmentCycle Assessment


•• Category 1Category 1——LeadershipLeadership 120 points120 points

•• Category 2Category 2——Strategic PlanningStrategic Planning 85 points85 points

•• Category 3Category 3——Customer and Market FocusCustomer and Market Focus 85 points85 points

•• Category 4Category 4——Information and AnalysisInformation and Analysis 90 points90 points

•• Category 5Category 5——Human Resource FocusHuman Resource Focus 85 points85 points

•• Category 6Category 6——Process ManagementProcess Management 85 points85 points

•• Category 7Category 7——Business ResultsBusiness Results 450 points450 points

Criteria for Criteria for Performance Performance ExcellenceExcellence


•• LeadershipLeadership——Leadership system, values, Leadership system, values, expectations, and public responsibilities expectations, and public responsibilities

•• Strategic PlanningStrategic Planning——The effectiveness of The effectiveness of strategic and business planning and deployment strategic and business planning and deployment of plans, focusing on performance requirements of plans, focusing on performance requirements

•• Customer and Market FocusCustomer and Market Focus——How the company How the company determines customer and market requirements and achievesdetermines customer and market requirements and achievescustomers satisfactioncustomers satisfaction

•• Information and AnalysisInformation and Analysis——The effectiveness of The effectiveness of information systems to support customer driven performance information systems to support customer driven performance excellence and marketplace success excellence and marketplace success

•• Human Resource FocusHuman Resource Focus——The success of efforts to realize The success of efforts to realize the full potential of the work force to create a highthe full potential of the work force to create a high--performance performance organization organization

•• Process ManagementProcess Management——The effectiveness of systems and The effectiveness of systems and processes for assuring the quality of products and services processes for assuring the quality of products and services

•• Business ResultsBusiness Results——Performance results and competitive Performance results and competitive benchmarking in customer satisfaction, financials, human benchmarking in customer satisfaction, financials, human resources, suppliers, and operations resources, suppliers, and operations

Documents

Process Performance and Quality - Faculty of Engineering ...adfisher/7943-05/Chpt5/ch05.pdf · Process Performance and Quality ... To Accompany Krajewski & Ritzman Operations Management: