Six Sigma Class Intro and Ppt

INTRODUCTION TO SIX SIGMA CONTENT FLOW†¦ ? Understanding Six Sigma ? Definition ? World at Six Sigma examples ? Six Sigma Scale ? Why Six Sigma ? Six Sigma Methodologies & Tools ? Define ? Measure ? Analyze ? Improve ? Control WHAT’S IN A NAME? Sigma is the Greek letter representing the standard deviation of a population of data. ? Sigma is a measure of standard deviation (the data spread) ? ? ? SIX SIGMA IS †¦ ? A statistical concept that measures a process in terms of defects – at the six sigma level, there 3. 4 defects per million opportunities ?A defect is anything that results in customer dissatisfaction Six Sigma is a methodology and a symbol of quality ? HOW OFTEN ARE WE DELIVERING ON TIME? ? If the target time is 30 Mins, the graphs below show two curves with average at 25 Mins 30 mins 30 mins s s 0 10 x 30 2 sigma 20 40 50 0 10 20 x 30 4 sigma 40 50 ? ? How many standard deviations can you â€Å"fit† within customer expectations? Managing by th e average doesn’t tell the whole story. The average and the variation together show what’s happening. MANAGING UP THE SIGMA SCALE Sigma 1 2 3 4 5 6 % Good % Bad 30. 9% 69. % 93. 3% DPMO 691,462 308,538 66,807 69. 1% 30. 9% 6. 7% 99. 38% 99. 977% 0. 62% 0. 023% 6,210 233 3. 4 99. 9997% 0. 00034% EXAMPLES OF THE SIGMA SCALE In a world at 3 sigma. . . ? In a world at 6 sigma. . . ? There are 964 U. S. flight cancellations per day. The police make 7 false arrests every 4 minutes. 1 U. S. flight is cancelled every 3 weeks. There are fewer than 4 false arrests per month. ? ? ? In one hour, 47,283 international long distance calls are accidentally disconnected. ? It would take more than 2 years to see the same number of dropped international calls.WHY SIX SIGMA? †¢ At GE, Six Sigma added more than $ 2 billion to the bottom line in 1999 alone †¢ Motorola saved more than $ 15 billion in the first 10 years of its Six Sigma effort AlliedSignal reports saving $ 1,5 billi on through Six Sigma. †¢ †¢ Six Sigma is about practices that help you eliminate defects and always deliver products and services that meet customer specifications How are these savings realized? cost of scrap? cost of rework? cost of excessive cycle times and delays? Benefits of added capacity and man-hoursDMAIC – THE IMPROVEMENT METHODOLOGY Define Objective: DEFINE the opportunity Measure Analyze Improve Control Objective: Objective: Objective: MEASURE current ANALYZE the root IMPROVE the performance causes of problems process to eliminate root causes Key Measure Tools: †¢ Critical to Quality Requirements (CTQs) †¢ Sample Plan †¢ Capability Analysis †¢ Failure Modes and Effect Analysis (FMEA) Key Analyze Tools: †¢ Histograms, Boxplots, MultiVari Charts, etc. †¢ Hypothesis Tests †¢ Regression Analysis Objective: CONTROL the process to sustain the gains.Key Define Tools: †¢ Cost of Poor Quality (COPQ) †¢ Voice of the Stak eholder (VOS) †¢ Project Charter †¢ As-Is Process Map(s) †¢ Primary Metric (Y) Key Improve Key Control Tools: Tools: †¢ Solution Selection †¢ Control Charts Matrix †¢ Contingency †¢ To-Be Process and/or Action Map(s) Plan(s) DEFINE – DMAIC PROJECT WHAT IS THE PROJECT? $ Project Charter Cost of Poor Quality Stakeholders Voice of the Stakeholde r Six Sigma What is the problem? The â€Å"problem† is the Output ? What is the cost of this problem ? Who are the stake holders / decision makers ?Align resources and expectations ? DEFINE – CUSTOMER REQUIREMENTS WHAT ARE THE CTQS? WHAT MOTIVATES CUSTOMER? SECONDARY RESEARCH Market Data THE Voice of the Customer Key Customer Issue Critical to Quality Listening Posts Industry Intel Industry Benchmarking Customer Service Customer Correspondence PRIMARY RESEARCH Survey s OTM Observations Focus Groups MEASURE – BASELINES AND CAPABILITY WHAT IS OUR CURRENT LEVEL Sample some data / not a ll data Current Process actuals measured against the Customer expectation OF PERFORMANCE?Descriptive Statistics Variable: 2003 Output Anderson-Darling Normality Test A-Squared: P-Value: Mean StDev Variance Skewness Kurtosis N Minimum 1st Quartile Median 3rd Quartile Maximum 0. 211 0. 854 23. 1692 10. 2152 104. 349 0. 238483 0. 240771 100 0. 2156 16. 4134 23. 1475 29. 6100 55. 2907 ? ? ? What is the chance that we will succeed at this level every time? 0 10 20 30 40 50 95% Confidence Interval for Mu 95% Confidence Interval for Mu 21. 1423 19. 5 20. 5 21. 5 22. 5 23. 5 24. 5 25. 5 26. 5 25. 1961 95% Confidence Interval for Sigma 8. 690 11. 8667 95% Confidence Interval for Median 95% Confidence Interval for Median 19. 7313 26. 0572 ANALYZE – VALIDATED ROOT CAUSES WHAT ARE THE KEY ROOT CAUSES? Experimental Design Data Stratification Regression Analysis Process Simulatio n Six Sigma y = f (x1, x2, x3 . . . xn) Critical Xs IMPROVE – POTENTIAL SOLUTIONS HOW CAN WE ADDRESS THE ROOT CAUSES IDENTIFIED? ? WE Address the causes, not the symptoms. Generate Evaluate Clarify Decision y = f (x1, x2, x3 . . . xn) Critical Xs Divergent | Convergent IMPROVE – SOLUTION SELECTIONHOW DO WE CHOOSE THE BEST SOLUTION? Solution Selection Matrix Qualit y Solution Sigma Time CBA Other Score Time Cost Six Sigma Solution Right Wrong Implementation Good Bad O Nice Idea Nice Try X Solution Implementatio n Plan CONTROL – SUSTAINABLE BENEFITS HOW DO WE †HOLD THE GAINS† OF OUR NEW PROCESS? ? ? Some variation is normal and OK How High and Low can an â€Å"X† go yet not materially impact the â€Å"Y† Pre-plan approach for control exceptions Direct Process Customer: CCR: Date: Measuring and Monitoring Loan Service Manager ? Process Owner: Process Description:Process Control System (Business Process Framework) Flowchart Customer Sales Processing Branch Manager Key Measure ments P1 – activity duration, min. Specs &/or Targets Measures (Too ls) Responsibility Contingency Where & (Who) (Quick Fix) Frequency 35 Remarks UCL=33. 48 Review appliation for completeness P2 – # of incomplete loan applications Individual Value Apply for loan 1. 1 Application & Review 25 Complete meeting information Mean=24. 35 No Application Complete? 1. 2 Processing 1. 3 Credit review 15 0 10 20 30 LCL=15. 21 1. 5 Disclosure 1. 4 Review Observation Number