Post on 30-Mar-2015
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Prepared by Dr. Leonard R. HeppAll Rights Reserved
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Prepared by Dr. Leonard R. HeppAll Rights Reserved
A Methodology … For Continuous Improvement
Six Sigma is a highly disciplined data-based methodology of problem solving leveraging tools & techniques where appropriate.
What is Six Sigma?
Six Sigma follows two rigorous approaches:
DMAIC Methodology …for improving EXISTING processes
DMADOV Methodology …for CREATING a new product or process
Let’s Look At Each Method
Define Measure Analyze Improve Control
VerifyDefine Measure Analyze Design Optimize
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Prepared by Dr. Leonard R. HeppAll Rights Reserved
Six Sigma: Key Terms
Critical to Quality Customer Performance Requirements
Characteristic (CTQ) of a Product or Service
Defect Any Event That Does NOT Meet the
Performance Specifications of a CTQ
Defect Opportunity Any Event Which Can Be Measured
That Provides a Chance of Not Meeting
a Customer Requirement
Concept of Defects is at the Core of Six Sigma!Concept of Defects is at the Core of Six Sigma!
Concept Definition
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Target
CustomerSpecification
X XXX X XX XXXX
XX
XXXXX
XX
XX
XX
X
XXX
XX
XX XXX
XXXX X
X
X
X
Every Human Activity Has Variability...
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defects
Variation & Defects are the Enemy
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Target CustomerSpecification
1
2
3
A 3 process because 3 standard deviations fit between target and spec
Target
CustomerSpecification
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34
56
6“No Defects”
Reliability thru Variance Reduction
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And … What About Discrete Data?
We have an Invoice Payment Process of 45 Days or less and recent data for last month shows that of 100 invoices, 92 were paid in 45 days or less.
92% “On Time”
Question…How many were paid in 30 days? Between 40-45 Days? What was my shortest payment cycles?
With Discrete Data you’d have to go back and re-measure! With Discrete Data you’d have to go back and re-measure! And you can’t model new performance limits. And…And you can’t model new performance limits. And…
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Average CustomerSpecification
63.4 Defects per
Million Opportunities6
_________________________________________________________________________
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AverageCustomer
Specification
67,000 Defects per Million Opportunities3
Considerations
• Customer Specification
• Average
• Variation
Six Sigma - A Stretch GoalFor many processes
BUTNot Good Enough for Some!
What is Six Sigma Quality?
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Sigma is a statistical unit of measure that reflects
process capability
DPMODPMO
6 3.4 99.9997%
5 233 99.98%
4 6,210 99%
3 66,807 93%
2 308,537 69%
%%
ProcessCapability
Defects Per MillionOpportunities
PercentageGood
Increase Requires Exponential DPMO Reduction
What is Six Sigma Quality?
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1,000,000
10,000
1,000
100
10
1
Sigma Scale of Measure
Restaurant Bills
Doctor Prescription Writing
Order Write-up
Domestic AirlineFatality Rate(0.43 PPM)
Airline Baggage Handling
“Average”IndustrialCompany
Best-in-ClassIndustrial Company
Defectsper
Million
3 4 5 6 72
“Typical” Service Industry Processes are 1.5 to 3
IRS Tax Advice(phone in)
Sigma Quality Level - Examples
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MeasureMeasure
AnalyzeAnalyze
ImproveImprove
DefineDefine
Six Sigma DMAIC Process
ControlControl
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Characterization
Optimization
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CharacterizationCharacterization
OptimizationOptimization
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MeasureMeasure
AnalyzeAnalyze
ImproveImprove
DefineDefine
ControlControl
Six Sigma DMAIC Overview
Practical Problem: Low Yield
Statistical Problem: Mean Off Target
Statistical Solution: Isolate Key Variables
Practical Solution: Install Automatic Controller
Practical SolutionPractical Solution
Statistical SolutionStatistical Solution
Practical ProblemPractical ProblemProblem Solving
FlowNeed
Need
Need
Need
Statistical ProblemStatistical Problem
Do
Do
Do
Practical ProblemWhat’s The Problem?
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Six Sigma DMAIC The 12+3 Step DMAIC Strategy
DMAIC – The 12 + 3 Steps
Formulating the Practical ProblemFormulating the Practical Problem
Changing to a Statistical ProblemChanging to a Statistical Problem
Developing a Statistical SolutionDeveloping a Statistical Solution
Implementing the Practical SolutionImplementing the Practical Solution
Step 0: Build the House of Quality
A. Identify Needs B. Team Charter C. Process/SIPOC
Step 1: Select the CTQ Characteristic
Step 2: Define Performance Standards
Step 3: Validate MSA and Data Collection
DMAIC
DMAIC
DMAIC
DMAIC
Step 4: Establish Process Capability
Step 5: Define Performance Objectives
Step 6: Identify Variation Sources
DMAIC
DMAIC
DMAIC
Step 7: Screen Potential Causes
Step 8: Discover Variable Relationships
Step 9: Establish Operating Tolerances
DMAIC
DMAIC
DMAIC
Step 10: Validate MSA on the Xs
Step 11: Determine Process Capability
Step 12: Implement Process Controls
DMAIC
DMAIC
DMAIC
How good am I today?
How good do I need to be?
What factors make a difference?
How good am I today?
How good do I need to be?
What factors make a difference?
How do my customers look at me?How do my customers look at me?
What do I want to improve?
What’s the best way to measure?
Can I trust the output data?
What do I want to improve?
What’s the best way to measure?
Can I trust the output data?
What’s at the root of the problem?
How can I predict the output?
How tight does the control have to be?
What’s at the root of the problem?
How can I predict the output?
How tight does the control have to be?
Can I trust the in-process data?
Have I reached my goal?
How can I sustain the improvement?
Can I trust the in-process data?
Have I reached my goal?
How can I sustain the improvement?
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Define Measure Analyze Improve ControlDefine Measure Analyze Improve Control
MeasureMeasure ImproveImprove ControlControlAnalyzeAnalyze
A. Customer A. Customer FocusFocus--CTQsNeeds
B. Team B. Team CharterCharter
C. Process C. Process MappingMapping
DefineDefine
Define The ProblemDefine The Problem
• Collect VOC• Define Customer Needs
• Business Case• Problem & Goal
Statements• Project Timeline• Team Members
Project Scope
• 5-7 High Level Steps
• Validated by Process Owner
MeasureMeasure ImproveImprove ControlControlAnalyzeAnalyze
A. Customer A. Customer FocusFocus--CTQsNeeds
B. Team B. Team CharterCharter
C. Process C. Process MappingMapping
DefineDefine
Define The ProblemDefine The Problem
• Collect VOC• Define Customer Needs
• Business Case• Problem & Goal
Statements• Project Timeline• Team Members
Project Scope
• 5-7 High Level Steps
• Validated by Process Owner
DefineDefine MeasureMeasure ImproveImprove ControlControlAnalyzeAnalyze
1. Select CTQ 1. Select CTQ CharacteristicsCharacteristicsMeasurementMeasurement
2. Define 2. Define Performance Performance
StandardsStandards
3. Validate 3. Validate Measurement Measurement
SystemSystem
Frame as a Practical ProblemFrame as a Practical Problem
• Quality Function Deployment (QFD)
• Select Key Output Metric “Y”
• Customer Specification Limits
• Targets
• Measurement Systems Analysis
• Data Collection Plan
5. Define 5. Define Performance Performance ObjectivesObjectives
6. Identify 6. Identify Variation Variation SourcesSources
4. Establish 4. Establish Performance Performance
CapabilityCapability
DefineDefine MeasureMeasure ImproveImprove ControlControlAnalyzeAnalyze
Frame as a DataFrame as a Data--Based ProblemBased Problem
• Baseline Current Process Performance
• Set Improvement Goal
• Identify Potential Root Causes
• Hypothesis Testing and Detailed Process Analysis
DefineDefine MeasureMeasure ImproveImprove ControlControlAnalyzeAnalyze
7. Screen 7. Screen Potential Potential CausesCauses
9. Establish 9. Establish Operating Operating
TolerancesTolerances
8. Discover 8. Discover Variable Variable
RelationshipsRelationships
Frame as a DataFrame as a Data--Based SolutionBased Solution
• Determine Root Cause
• Design Improvement Solution
• Pilot Solution
DefineDefine MeasureMeasure ImproveImprove ControlControlAnalyzeAnalyze
10. Validate 10. Validate Measurement Measurement
System (on XSystem (on X’’s)s)
12. Implement 12. Implement Process Process ControlsControls
11. Determine 11. Determine New Process New Process
CapabilityCapability
Frame as a Practical SolutionFrame as a Practical Solution
• Measurement System Analysis
• Improved Process Performance
• Control Plans & Dashboards
• Documentation• Process
Management Plan
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Yes
Yes
AnalyzeMeasure Improve ControlDefine
Is the Improvement
a New or Redesigned
Product/Service?
Is the Improvement
a New or Redesigned
Product/Service?
AnalyzeMeasure Design VerifyDefine
IsIncremental
Improvement Enough?
IsIncremental
Improvement Enough?
Does a Process Exist?
Does a Process Exist?
NoNo
Yes No
DMAIC/DMADOV Transition Points:
Optimize
When To Use DMADOV
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Design For Six SigmaDesign For Six SigmaDesign For Six Sigma
DefineDefineDefine MeasureMeasureMeasure AnalyzeAnalyzeAnalyze DesignDesignDesign VerifyVerifyVerify
Develop Detailed Design And Control/Test Plan
Develop Detailed Design And Control/Test Plan
Implement Full-Scale Processes and Document Control Plans
Implement Full-Scale Processes and Document Control Plans
Initiate, Scope, And Plan The Project
Initiate, Scope, And Plan The Project
Understand Customer Needs And Specify CTQs
Understand Customer Needs And Specify CTQs
Develop Design Concepts And High-Level Design
Develop Design Concepts And High-Level Design
OptimizeOptimizeOptimize
Test Design, Optimize and validate performance to CTQs
Test Design, Optimize and validate performance to CTQs
VerifyDefine Measure Analyze Design Optimize VerifyDefine Measure Analyze Design Optimize
DMADOV – The 5 Phases and 14 Steps
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1. Identify customer needs (CTQ’s) and set performance goals.
8. Generate and validate models - Identify transfer functions.9. Capability flow-up utilizing scorecards…watch for:
• Low Zst on scorecard.• Lack of transfer function.• Unknown process capability.
10. Optimize design• Statistical analysis of variance drivers• Robustness• Error proofing
11. Generate process specs and verify measurement system X’s
12. Statistically confirm predictions.13. Develop control plan for CTQ’s (mean and variance).14. Document the effort and results.
The DMADOV Methodology – 14 Steps
2. Perform QFD/CTQ flowdown…Needs to Design Requirements 3. Establish measurement system capability.
4. Develop conceptual designs5. Reliability Analysis of Designs6. Build Scorecard of Customer Needs (CTQ’s)7. Perform risk assessment
QUALITY BY DESIGN!QUALITY BY DESIGN!
DMADOV DMADOV FundamentalsFundamentals(Key Concepts)(Key Concepts)
QFD-CTQFlow-Down
FMEA
Business Model (Transfer Function)
Scorecards
AnalyzeAnalyze
DesignDesign
OptimizeOptimize
VerifyVerify
DefineDefine
MeasureMeasure
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VerifyDefine Measure Analyze Design Optimize VerifyDefine Measure Analyze Design Optimize
Step 1: Identify Customer CTQ’s and Set Quality Goals
DEFINE
ID Service or Product Issue
Business Case
Problem/Goal Statement
Project Leadership/Team
ID Customers
Gather Customer Needs
Rank/Prioritize Needs
Project Scope Review
MGPP
Resources/ Team Assessment
Project Management Approach
Project Plan and Timelines
Organization Challenges
Plan & Manage the
ProjectInitiate the
Project
ID Customers & Gather
NeedsScope the
Project
Key Focus Areas
DMADOV
MSA Analysis• GR&R – Precision
• Accuracy
• Linearity
• Stability
Baseline-Sigma and/or Zscores
Legal and Regulatory
Organize and Prioritize Customer Needs
Determine Project CTQ’s
Flow-Down of CTQ’s by QFD
Perform CTQ Flow-Down Establish MSA and Baseline
Step 2: Perform QFD/CTQ Flowdown
Step 3: Establish Measurement System Capability & Baseline
MEASURE
Key Focus Areas
DMADOV
Step 4: Develop Conceptual Designs
Step 5: Reliability Analysis of Designs
Step 6: Build Scorecards of CTQ’s
Step 7: Perform Risk Analysis
High Level Design and Process Focus
Requirements for Process, IT, Facilities, HR, etc.
Assess Capability via CTQ Flow-Down & Flow-Up
Select Best-Fit Design
Customer Feedback
Risk & Patent Reviews
Functional Analysis
Alternate Design Reviews
Develop Design Concepts
Develop High Level Designs
Evaluate High Level Design Capability
Key Focus Areas
ANALYZE DMADOV
Step 8: Generate & Validate Models • Develop Transfer Function
Step 9: Capability Flow-Up Utilizing Scorecards• Low Zst on Scorecard• Lack of Transfer Function• Unknown Process Capability
Predict & Improve Design Capability
Design Reviews & Risk Assessment
Control Strategy Plan
Test & Validate Control Plan
Pilot Process Review
Design Elements to meet Functional CTQs
Detailed Process Elements
Determine & Measure CTPs
Develop Detailed Design
Evaluate Detailed Design Capability
Prepare Control & Verification Plan
DMADOV
Watch for These!
Key Focus Areas
DESIGN
Step 10: Optimize Design• Statistical Analysis of Variance Drivers• Robustness• Error Proofing
Step 11: Generate Process Specs & Verify MSA on the X’s
Business Model (Transfer Function)
MSA on System X’s
Pilot & Assess Variance
Robustness & Error Proofing
Pilot Process & Test to ScoreCard
Optimize Design Process Specs and MSA
Key Focus Areas
OPTIMIZE DMADOV
Step 12: Statistically Determine Predictions
Step 13: Develop Control; Plans for CTQs (Mean & Variance)
Step 14: Document Efforts and Results
Build Full Scale Process
Scale-Up & Test
Verify Performance
Turnover to Ops & Maintenance
Transition to Process Owners
Project Close
Build Pilot Scale Process
Pilot Test & Evaluate
Implement Planning
Execute Pilot and Analyze Results
Implement Production Process
Transition to Process Owners
Key Focus Areas
VERIFY DMADOV
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Project Charter
Problem Statement & Goal
Project Scope
Project Milestones (with firm dates for DMA, targets for DOV)
High-Level CTQ’s
Project Team (Leader, Champion, Sponsor, Black Belt, Master Black Belt, Team Members, Other Resources)
Internal Communication Plan
Business Case
Project Risk Assessment (FMEA or written assessment)
Multi-Generational Plan
Cost-Benefit Analysis
Identify, segment & prioritize customer
User Profiling (how many, how often, from where)
Identify & prioritize CTQ’s
Interviews, surveys, or focus groups
Measurement Plan
Acceptance Criteria
As-Is Process Documentation
QFD to determine how to satisfy CTQ’s
Benchmarking (within your team, within company, external)
To-Be Process Map/High-Level Solution
Make vs. Buy Analysis
Vendor/Technology Selection
Detailed Functional Specification
Prototype (use to iteratively refine functional specification)
Define Test Cases
Final Project Schedule and Project Plan
Phased Rollout Schedule
End-User Communication and Marketing Plan
Technical Specification
Interface Design
Application Architecture
Information Architecture (DB)
Server Architecture
Code Reuse Strategy
System FMEA
Security Plan (engage SSO team)
Backup & DR Plan
Monitoring Solution
Peer Technical Reviews
Packaged Software Customization Review
Help Desk Strategy
Purchase Hardware and Software
Schedule Stress Test and Security Review
Code Application
Develop User & Training Documentation
System Documentation
Application Kit (for Production Support)
Help Desk Documentation
Unit Test
Integration Test
Browser Lab Test
Peer Code Review
Freeze Code
Performance & Load Test
Security Code Review
Data Migration
Production Deployment
Preliminary Acceptance Testing
Launch Monitoring Tools
User Training
Production Pilot
Update System FMEA
Transition to Production Support
Transition to Help Desk
GO LIVE
Performance and Usage Monitoring
Issues Log
Feedback Management
Bug Fixes and Further Optimization
Final Acceptance Testing and CTQ Measurement
Document & Share Best Practices
DMADOV Project Progress Overview
Define Measure Analyze Optimize Verify Design