chapter 5 quality
DESCRIPTION
Chapter 5 Quality. Learning Objectives. Be Able to Apply Concepts in Learning Goals Determine Product Reliability Construct and Interpret Control Charts Determine Process Capability Be Able to Use Equations Listed in End of Chapter Equation Summary. Continuous improvement. - PowerPoint PPT PresentationTRANSCRIPT
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Chapter 5 Chapter 5
QualityQuality
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Learning Objectives• Be Able to Apply Concepts in Learning
Goals• Determine Product Reliability• Construct and Interpret Control Charts• Determine Process Capability• Be Able to Use Equations Listed in End
of Chapter Equation Summary
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TQMTQMWheelWheel
Customer satisfaction
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TQMTQMWheelWheel
Customer satisfaction
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Customer-DrivenCustomer-DrivenDefinitions of QualityDefinitions of Quality Conformance to SpecificationsConformance to Specifications ValueValue Fitness for UseFitness for Use SupportSupport Psychological ImpressionsPsychological Impressions
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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
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EmployeeEmployeeInvolvementInvolvement Cultural ChangeCultural Change TeamsTeams Individual DevelopmentIndividual Development Awards and IncentivesAwards and Incentives
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PlanPlan
DoDo
CheckCheck
ActAct
DemingDemingWheelWheel
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ReliabilityReliabilityProduct reliabilityProduct reliability
rrss == ( (rr11)()(rr22) . . . () . . . (rrnn))wherewhere
rrss = = reliability of the complete reliability of the complete productproductnn = = number of subsystemsnumber of subsystemsrrnn = = reliability of the subsystem reliability of the subsystem or component or component nn
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ReliabilityReliabilityProduct reliabilityProduct reliability
rrss == ( (rr11)()(rr22) . . . () . . . (rrnn))wherewhere
rrss = = reliability of the complete reliability of the complete productproductnn = = number of subsystemsnumber of subsystemsrrnn = = reliability of the subsystem reliability of the subsystem or component or component nn
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ReliabilityReliabilityProduct reliabilityProduct reliability
rrss == ( (rr11)()(rr22) . . . () . . . (rrnn))wherewhere
rrss = = reliability of the complete reliability of the complete productproductnn = = number of subsystemsnumber of subsystemsrrnn = = reliability of the subsystem reliability of the subsystem or component or component nn
rrss = (0.99)(0.90)(0.85) = 0.76 = (0.99)(0.90)(0.85) = 0.76
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ReliabilityReliabilityProduct reliabilityProduct reliability
rrss == ( (rr11)()(rr22) . . . () . . . (rrnn))wherewhere
rrss = = reliability of the complete reliability of the complete productproductnn = = number of subsystemsnumber of subsystemsrrnn = = reliability of the subsystem reliability of the subsystem or component or component nn
rrss = (0.99)(0.90)(0.85) = 0.76 = (0.99)(0.90)(0.85) = 0.76
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ReliabilityReliabilityProduct reliabilityProduct reliability
rrss == ( (rr11)()(rr22) . . . () . . . (rrnn))wherewhere
rrss = = reliability of the complete reliability of the complete productproductnn = = number of subsystemsnumber of subsystemsrrnn = = reliability of the subsystem reliability of the subsystem or component or component nn
rrss = (0.99)( = (0.99)(0.950.95)()(0.900.90) = ) = 0.850.85
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ReliabilityReliabilityProduct reliabilityProduct reliability
rrss == ( (rr11)()(rr22) . . . () . . . (rrnn))wherewhere
rrss = = reliability of the complete reliability of the complete productproductnn = = number of subsystemsnumber of subsystemsrrnn = = reliability of the subsystem reliability of the subsystem or component or component nn
rrss = (0.99)(0.95)(0.90) = 0.85 = (0.99)(0.95)(0.90) = 0.85
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QualityQualityFunctionFunctionDeploymentDeployment
The House of QualityThe House of Quality
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QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
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QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
Competitive Competitive AnalysisAnalysis
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QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
Voice of Voice of the the
EngineerEngineer
Competitive Competitive AnalysisAnalysis
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QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
Voice of Voice of the the
EngineerEngineer
Trade-offsTrade-offs
Competitive Competitive AnalysisAnalysis
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
Voice of Voice of the the
EngineerEngineer
Trade-offsTrade-offs
Competitive Competitive AnalysisAnalysis
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
Voice of Voice of the the
EngineerEngineer
CorrelationsCorrelationsCompetitive Competitive
AnalysisAnalysis
Trade-offsTrade-offs
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
Voice of Voice of the the
EngineerEngineer
CorrelationsCorrelations
Trade-offsTrade-offs
Competitive Competitive AnalysisAnalysis
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
Voice of Voice of the the
EngineerEngineer
CorrelationsCorrelations
Technical ComparisonTechnical Comparison
Trade-offsTrade-offs
Competitive Competitive AnalysisAnalysis
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
QualityQualityFunctionFunctionDeploymentDeployment
Voice of Voice of the the
CustomerCustomer
Competitive Competitive AnalysisAnalysis
Voice of Voice of the the
EngineerEngineer
CorrelationsCorrelations
Technical ComparisonTechnical Comparison
Trade-offsTrade-offs
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PlanningPlanning AnalysisAnalysis IntegrationIntegration ActionAction
BenchmarkingBenchmarking
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Data Analysis Data Analysis ToolsTools
• ChecklistsChecklists• Histograms and Bar ChartsHistograms and Bar Charts• Pareto ChartsPareto Charts• Scatter DiagramsScatter Diagrams• Cause-and-Effect DiagramsCause-and-Effect Diagrams• GraphsGraphs
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Wellington Fiber Board Co.Wellington Fiber Board Co.Tools for Improving QualityTools for Improving Quality
Step 1—ChecklistStep 1—Checklist Step 2—Pareto chartStep 2—Pareto chart Step 3—Cause-and-effect diagramStep 3—Cause-and-effect diagram Step 4—Bar chartStep 4—Bar chart
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Wellington Fiber Board Co.Wellington Fiber Board Co.ChecklistsChecklists
Headliner Defects Defect type Tally Total
A. Tears in fabricB. Discolored fabricC. Broken fiber board
D. Ragged edges Total
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Wellington Fiber Board Co.Wellington Fiber Board Co.ChecklistsChecklists
Headliner Defects Defect type Tally Total
A. Tears in fabricB. Discolored fabricC. Broken fiber board /
D. Ragged edges Total
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Wellington Fiber Board Co.Wellington Fiber Board Co.ChecklistsChecklists
Headliner Defects Defect type Tally Total
A. Tears in fabricB. Discolored fabricC. Broken fiber board //
D. Ragged edges Total
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Wellington Fiber Board Co.Wellington Fiber Board Co.ChecklistsChecklists
Headliner Defects Defect type Tally Total
A. Tears in fabric /B. Discolored fabricC. Broken fiber board //
D. Ragged edges Total
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Wellington Fiber Board Co.Wellington Fiber Board Co.ChecklistsChecklists
Headliner Defects Defect type Tally Total
A. Tears in fabric /B. Discolored fabricC. Broken fiber board //
D. Ragged edges / Total
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Wellington Fiber Board Co.Wellington Fiber Board Co.ChecklistsChecklists
Headliner Defects Defect type Tally Total
A. Tears in fabric //// 4B. Discolored fabric /// 3C. Broken fiber board //// //// //// ////
//// //// //// / 36D. Ragged edges //// // 7
Total 50
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Wellington Fiber Board Co.Wellington Fiber Board Co.Pareto ChartPareto Chart
Num
ber o
f def
ects
100
80
60
40
20
0
50
40
30
20
10
0
Cum
ulat
ive
perc
enta
ge
Defect type
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Wellington Fiber Board Co.Wellington Fiber Board Co.Pareto ChartPareto Chart
Num
ber o
f def
ects
100
80
60
40
20
0
50
40
30
20
10
0
Cum
ulat
ive
perc
enta
ge
Defect type
C
DA B
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Wellington Fiber Board Co.Wellington Fiber Board Co.Pareto ChartPareto Chart
Num
ber o
f def
ects
100
80
60
40
20
0
50
40
30
20
10
0
Cum
ulat
ive
perc
enta
ge
Defect type
C
DA B
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Wellington Fiber Board Co.Wellington Fiber Board Co.Cause-and-Effect DiagramCause-and-Effect Diagram
Out of specification Not available
Training Absenteeism Communication
HumiditySchedule changes
Machine maintenance Machine speedWrong setup
Process
People
Other
Materials
Broken fiber
board
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Wellington Fiber Board Co.Wellington Fiber Board Co.Bar ChartBar Chart
20
15
10
5
0
Num
ber o
f bro
ken
fiber
boa
rds
First Second ThirdShift
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Sample Means and theSample Means and theProcess DistributionProcess Distribution
425 Grams
Mean
Processdistribution
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Sample Means and theSample Means and theProcess DistributionProcess Distribution
Processdistribution
425 Grams
MeanDistribution ofsample means
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Control ChartsControl ChartsUCL
Nominal
LCL
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Control ChartsControl ChartsUCL
Nominal
LCL
1 2 3Samples
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Control ChartsControl ChartsUCL
Nominal
LCL
1 2 3Samples
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Control ChartsControl ChartsUCL
Nominal
LCL
Assignable causes likely
1 2 3Samples
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Using Control Charts for Using Control Charts for Process ImprovementProcess Improvement
Measure the process When changes are indicated,
find the assignable cause Eliminate problems, incorporate
improvements Repeat the cycle
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Control Chart ExamplesControl Chart Examples
Nominal
UCL
LCL
Sample number
Varia
tions
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control Chart ExamplesControl Chart Examples
Nominal
UCL
LCL
Sample number
Varia
tions
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control Chart ExamplesControl Chart Examples
Nominal
UCL
LCL
Sample number
Varia
tions
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control Chart ExamplesControl Chart Examples
Nominal
UCL
LCL
Sample number
Varia
tions
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control Chart ExamplesControl Chart Examples
Nominal
UCL
LCL
Sample number
Varia
tions
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control Charts TypesControl Charts Types• Control charts for attributes
– Yes/no– Off/on
• Control charts for variables– Length– Width– Weight
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Control ChartsControl Chartsfor Variablesfor Variables
West Allis IndustriesWest Allis Industries
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Control ChartsControl Chartsfor Variablesfor Variables
Sample SampleNumber 1 2 3 4
12345
Special Metal Screw
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Control ChartsControl Chartsfor Variablesfor Variables
Sample SampleNumber 1 2 3 4
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 0.5047
Special Metal Screw
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Control ChartsControl Chartsfor Variablesfor Variables
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
_
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
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
_
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
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
0.5027 – 0.50090.5027 – 0.5009 == 0.00180.0018
Special Metal Screw
_
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Sample SampleNumber 1 2 3 4 R x
1 0.5014 0.5022 0.5009 0.5027 0.00182 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
0.5027 – 0.50090.5027 – 0.5009 == 0.00180.0018
Special Metal Screw
_
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Sample SampleNumber 1 2 3 4 R x
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
0.5027 – 0.50090.5027 – 0.5009 == 0.00180.0018(0.5014 + 0.5022 +(0.5014 + 0.5022 + 0.5009 + 0.5027)/40.5009 + 0.5027)/4 == 0.50180.5018
Special Metal Screw
_
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Sample SampleNumber 1 2 3 4 R x
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
0.5027 – 0.50090.5027 – 0.5009 == 0.00180.0018(0.5014 + 0.5022 +(0.5014 + 0.5022 + 0.5009 + 0.5027)/40.5009 + 0.5027)/4 == 0.50180.5018
Special Metal Screw
_
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Sample SampleNumber 1 2 3 4 R x
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
Special Metal Screw
_
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Sample SampleNumber 1 2 3 4 R x
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
=
_
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Control ChartsControl Chartsfor Variablesfor Variables
Control Charts – Special Metal ScrewR-Charts R = 0.0021
UCLR = D4RLCLR = D3R
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Control ChartsControl Chartsfor Variablesfor Variables Control Chart FactorsControl 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-Charts-Charts RR-Charts-Charts RR-Charts-Charts
((nn)) ((AA22)) ((DD33)) ((DD44))
22 1.8801.880 0 0 3.2673.26733 1.0231.023 0 0 2.5752.57544 0.7290.729 0 0 2.2822.28255 0.5770.577 0 0 2.1152.11566 0.4830.483 0 0 2.0042.00477 0.4190.419 0.076 0.076 1.9241.924
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Control ChartsControl Chartsfor Variablesfor Variables
Control Charts - Special Metal ScrewR - Charts R = 0.0020 D4 = 2.2080
Control Chart FactorsControl Chart FactorsFactor for UCLFactor for UCL Factor forFactor for FactorFactor
Size ofSize of and LCL forand LCL for LCL forLCL for UCL forUCL forSampleSample xx-Charts-Charts RR-Charts-Charts RR-Charts-Charts
((nn)) ((AA22)) ((DD33)) ((DD44))
22 1.8801.880 0 0 3.2673.26733 1.0231.023 0 0 2.5752.57544 0.7290.729 0 0 2.2822.28255 0.5770.577 0 0 2.1152.11566 0.4830.483 0 0 2.0042.00477 0.4190.419 0.076 0.076 1.9241.924
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Control ChartsControl Chartsfor Variablesfor Variables
Control Charts—Special Metal ScrewR-Charts R = 0.0021 D4 = 2.282
D3 = 0UCLR = D4RLCLR = D3R
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Control ChartsControl Chartsfor Variablesfor Variables
Control Charts—Special Metal ScrewR-Charts R = 0.0021 D4 = 2.282
D3 = 0
UCLR = 2.282 (0.0021) = 0.00479 in.
UCLR = D4RLCLR = D3R
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Control Charts—Special Metal ScrewR-Charts R = 0.0021 D4 = 2.282
D3 = 0
UCLR = 2.282 (0.0021) = 0.00479 in.LCLR = 0 (0.0021) = 0 in.
UCLR = D4RLCLR = D3R
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Control Charts—Special Metal ScrewR-Charts R = 0.0021 D4 = 2.282
D3 = 0
UCLR = 2.282 (0.0021) = 0.00479 in.LCLR = 0 (0.0021) = 0 in.
UCLR = D4RLCLR = D3R
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Range Chart - Range Chart - Special Metal ScrewSpecial Metal Screw
| | | | | | | |0 1 2 3 4 5 6 7
0.005 -0.0045 -
0.004 -0.0035 -
0.003 -0.0025 -
0.002 -0.0015 -
0.001 -0.0005 -
0 -
Ran
ge
R-Chart
Sample Number
UCLR = 0.00479
LCLR = 0
R = 0.0021
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Control ChartsControl Chartsfor Variablesfor Variables
Control Charts—Special Metal ScrewX-Charts
UCLx = x + A2RLCLx = x – A2R
==
R = 0.0021x = 0.5027=
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Control ChartsControl Chartsfor Variablesfor Variables
Control Charts - Special Metal ScrewR = 0.0020x = 0.5025
x - Charts
UCLx = x + A2RLCLx = x - A2R
Control Chart FactorsControl Chart FactorsFactor for UCLFactor for UCL Factor forFactor for FactorFactor
Size ofSize of and LCL forand LCL for LCL forLCL for UCL forUCL forSampleSample xx-Charts-Charts RR-Charts-Charts RR-Charts-Charts
((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 1.9241.924
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Control ChartsControl Chartsfor Variablesfor Variables
Control Charts—Special Metal Screwx- Charts
UCLx = x + A2RLCLx = x – A2R
==
R = 0.0021 A2 = 0.729x = 0.5027=
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Control Charts—Special Metal Screwx- Charts
UCLx = 0.5027 + 0.729 (0.0021) = 0.5042 in.
UCLx = x + A2RLCLx = x – A2R
==
R = 0.0021 A2 = 0.729x = 0.5027=
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control ChartsControl Chartsfor Variablesfor Variables
Control Charts—Special Metal Screwx- Charts
UCLx = 0.5027 + 0.729 (0.0021) = 0.5042 in.LCLx = 0.5027 – 0.729 (0.0021) = 0.5012 in.
UCLx = x + A2RLCLx = x – A2R
==
R = 0.0021 A2 = 0.729x = 0.5027=
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
xx-Chart—-Chart—Special Metal ScrewSpecial Metal Screw
| | | | | | | |0 1 2 3 4 5 6 7
0.505 -0.5045 -
0.504 -0.5035 -
0.503 -0.5025 -
0.502 -0.5015 -
0.501 -
Ave
rage
X-Bar Chart
Sample Number
UCLX = 0.5042
LCLX = 0.5012
X = 0.5027=
–
–
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
| | | | | | | |0 1 2 3 4 5 6 7
0.505 -0.5045 -
0.504 -0.5035 -
0.503 -0.5025 -
0.502 -0.5015 -
0.501 -
Ave
rage
X-Bar Chart
Sample Number
UCLX = 0.5042
LCLX = 0.5012
X = 0.5027=
–
–
xx-Chart— -Chart— Special Metal ScrewSpecial Metal Screw
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
| | | | | | | |0 1 2 3 4 5 6 7
0.505 -0.5045 -
0.504 -0.5035 -
0.503 -0.5025 -
0.502 -0.5015 -
0.501 -
Ave
rage
X-Bar Chart
Sample Number
UCLX = 0.5042
LCLX = 0.5012
X = 0.5027=
–
–
xx-Chart—-Chart—Special Metal ScrewSpecial Metal Screw
Measure the process Find the assignable cause Eliminate the problem Repeat the cycle
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Control Chart for Control Chart for AttributesAttributes• p-chart
– Used for controlling the proportion of defectives generated by a process
• c-chart– Used for controlling the number of
defects when more than one defect can be present in a particular product or service
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
p-chart(1 )
where:n = sample sizep = historical average proportion defective or target value
pp pn
where:z = normal deviate (std dev)
p p
p p
UCL p z
LCL p z
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c-chartc = mean of distribution
c standard deviation
where:z = normal deviate (std dev)
c
c
UCL c z c
LCL c z c
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Process CapabilityProcess CapabilityNominalvalue
800 1000 1200 Hours
Upperspecification
Lowerspecification
Process distribution
(a) Process is capable
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Process CapabilityProcess CapabilityNominalvalue
Hours
Upperspecification
Lowerspecification
Process distribution
(b) Process is not capable800 1000 1200
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Process CapabilityProcess Capability
Lowerspecification
Mean
Upperspecification
Two sigma
Nominal value
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Process CapabilityProcess Capability
Lowerspecification
Mean
Upperspecification
Four sigma
Two sigma
Nominal value
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Process CapabilityProcess Capability
Lowerspecification
Mean
Upperspecification
Six sigma
Four sigma
Two sigma
Nominal value
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
ISOISO90009000
ISOISO1400014000
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Category 1—Leadership
120 points Category 2—Strategic Planning
85 points Category 3—Customer and Market Focus
85 points Category 4—Information and Analysis
90 points Category 5—Human Resource Focus
85 points Category 6—Process Management
85 points Category 7—Business Results
450 points
Criteria for Criteria for Performance Performance ExcellenceExcellence
To Accompany Ritzman & Krajewski, Foundations of Operations Management © 2003 Prentice-Hall, Inc. All rights reserved.
Leadership—Leadership—Leadership system, values, expectations, and public responsibilities
Strategic Planning—Strategic Planning—The effectiveness of strategic and business planning and deployment of plans, focusing on performance requirements
Customer and Market Focus—Customer and Market Focus—How the company determines customer and market requirements and achievescustomers satisfaction
Information and Analysis—Information and Analysis—The effectiveness of information systems to support customer driven
performance excellence and marketplace success
Human Resource Focus—Human Resource Focus—The success of efforts to realize the full potential of the work force to create a high-
performance organization
Process Management—Process Management—The effectiveness of systems and processes for assuring the quality of products and services
Business Results—Business Results—Performance results and competitive benchmarking in customer satisfaction, financials, human resources, suppliers, and operations