Rev. 04/03/09 SJSU Bus. 142 - David Bentley

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Rev. 04/03/09 SJSU Bus. 142 - David Bentley

  1. 1. Week 11 - Six-Sigma Management and Tools 6 Σ Organization, DMAIC, Taguchi Method, Robust Design, Design of Experiments, Design for Six Sigma, Reasons for 6 Σ Failure Rev. 04/03/09 SJSU Bus. 142 - David Bentley
  2. 2. Topics 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>What is Six-Sigma? </li></ul><ul><li>Organizing Six-Sigma </li></ul><ul><li>DMAIC overview </li></ul><ul><li>DMAIC phases </li></ul><ul><li>The Taguchi method </li></ul><ul><li>Design for Six-Sigma </li></ul><ul><li>Using Six-Sigma from a contingency </li></ul><ul><li>perspective </li></ul>
  3. 3. Six Sigma Evolution <ul><li>Started as a simple quality metric at Motorola in 1986 ( Bill Smith ) </li></ul><ul><li>Migrated to Allied Signal </li></ul><ul><ul><li>(acquired Honeywell and took its name) </li></ul></ul><ul><li>Picked up by General Electric </li></ul><ul><ul><li>Commitment by CEO Jack Welch in 1995 </li></ul></ul><ul><ul><li>Grown to be an integrated strategy for attaining extremely high levels of quality </li></ul></ul>Rev. 11/15/07 SJSU Bus. 142 - David Bentley
  4. 4. What is Six-Sigma? Rev. 10/29/08 SJSU Bus. 142 - David Bentley <ul><li>Sigma (  ) is a Greek letter used to </li></ul><ul><li>designate a standard deviation ( SD ) in </li></ul><ul><li>statistics </li></ul><ul><li>Six refers to the number of SD ’ s from the </li></ul><ul><li>specialized limit to the mean. </li></ul><ul><li>Six sigma is a fairly recent umbrella approach to achieve quality </li></ul>
  5. 5. Percent Not Meeting Specifications <ul><li>+ 1 Σ = 32% </li></ul><ul><li>+ 2 Σ = 4.5% </li></ul><ul><li>+ 3 Σ = 0.3% </li></ul><ul><li>+ 6 Σ = 0.00034% </li></ul>11/13/07 SJSU Bus. 142 - David Bentley
  6. 6. Six-Sigma Levels 11/13/07 SJSU Bus. 142 - David Bentley Sigma Level Long-term ppm* defects 1 691,462 2 308,538 3 66,807 4 6,210 5 233 6 3.4
  7. 7. Statistics - DPU <ul><li>Defect </li></ul><ul><ul><li>Six Sigma: “any mistake or error passed on to the customer” ??? </li></ul></ul><ul><ul><li>General view: any variation from specifications </li></ul></ul><ul><li>DPU (defects per unit) </li></ul><ul><ul><li>Number of defects per unit of work </li></ul></ul><ul><ul><li>Ex: 3 lost bags ÷ 8,000 customers </li></ul></ul><ul><ul><li>= . 0 00375 </li></ul></ul>Rev. 11/10/08 SJSU Bus. 142 - David Bentley
  8. 8. Statistics – dpmo (defects per million opportunities) <ul><li>Process may have more than one opportunity for error (e.g., airline baggage) </li></ul><ul><li>dpmo = ( DPU × 1,000,000) ÷ </li></ul><ul><li>opportunities for error </li></ul><ul><li>Ex: ( 3 lost bags × 1,000,000) ÷ ( 8,000 customers × 1.6 average bags) </li></ul><ul><li>= 234.375 </li></ul><ul><li>or (.000375)(1,000,000) ÷ 1.6 = 234.375 </li></ul>Rev. 11/10/08 SJSU Bus. 142 - David Bentley
  9. 9. Statistics – dpmo (cont’d) <ul><li>May extend the concept to include higher level processes </li></ul><ul><ul><li>E.g., may consider all opportunities for errors for a flight (from ticketing to baggage claim) </li></ul></ul>11/13/07 SJSU Bus. 142 - David Bentley
  10. 10. Statistics - Off-Centering <ul><li>Represents a shift in the process mean </li></ul><ul><li>Impossible to always keep the process mean the same (this WOULD be perfection) </li></ul><ul><li>Does NOT represent a change in specifications </li></ul><ul><li>Control of shift within ± 1.5 σ of the target mean keeps defects to a maximum of 3.4 per million </li></ul>11/13/07 SJSU Bus. 142 - David Bentley
  11. 11. Statistics - Off-Centering (cont’d) Source: Evans & Lindsay, The Management and Control of Quality, Southwestern, 2005 11/13/07 SJSU Bus. 142 - David Bentley
  12. 12. k-Sigma Quality Levels <ul><li>Number of defects per million opportunities </li></ul><ul><ul><li>For a specified off-centering and </li></ul></ul><ul><ul><li>a desired quality level </li></ul></ul>Rev. 11/03/08 SJSU Bus. 142 - David Bentley
  13. 13. k-Sigma Quality Levels Source: Evans & Lindsay, The Management and Control of Quality, Southwestern, 2005 11/13/07 SJSU Bus. 142 - David Bentley
  14. 14. Six Sigma and Other Techniques 11/13/07 SJSU Bus. 142 - David Bentley <ul><ul><li>Six-Sigma is … designed to handle the most difficult quality problems. </li></ul></ul>% Quality Problems Techniques 90% Basic tools of Quality < 10% Six-Sigma < 1% Outside specialists
  15. 15. Organizing Six Sigma 11/13/07 SJSU Bus. 142 - David Bentley
  16. 16. Key Players 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Champion . Work with black belts to </li></ul><ul><li>identify possible projects </li></ul><ul><li>Master Black Belts . Work with and train </li></ul><ul><li>new black belts </li></ul><ul><li>Black Belts . Committed full time to </li></ul><ul><li>completing cost-reduction projects </li></ul><ul><li>Green Belts . Trained in basic quality </li></ul><ul><li>tools </li></ul>
  17. 17. Distribution of Six Sigma Trained Employees 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>In a company with 100 employees there might be: </li></ul><ul><li>One black belt </li></ul><ul><li>Sixty green belts </li></ul><ul><li>Some companies have yellow belts, employees </li></ul><ul><li>familiar with improvement processes </li></ul>
  18. 18. Six Sigma Tools DMAIC, Taguchi Method, Design for Six Sigma 11/13/07 SJSU Bus. 142 - David Bentley
  19. 19. DMAIC 11/13/07 SJSU Bus. 142 - David Bentley
  20. 20. DMAIC DMAIC Overview 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Stands for the six phases: </li></ul><ul><ul><li>D efine </li></ul></ul><ul><ul><li>M easure </li></ul></ul><ul><ul><li>A nalyze </li></ul></ul><ul><ul><li>I mprove </li></ul></ul><ul><ul><li>C ontrol </li></ul></ul>
  21. 21. D MAIC Define – (1) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Four Sub-Phases: </li></ul><ul><ul><li>Develop the business case </li></ul></ul><ul><ul><li>Project evaluation </li></ul></ul><ul><ul><li>Pareto analysis </li></ul></ul><ul><ul><li>Project definition </li></ul></ul>
  22. 22. D MAIC Define – (2) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Developing the Business Case: </li></ul><ul><ul><li>Identify a group of possible projects </li></ul></ul><ul><ul><li>Writing the business case </li></ul></ul><ul><ul><li>Stratifying the business case into problem statement and objective statement </li></ul></ul>
  23. 23. D MAIC Define – (3) Rev. 11/03/08 SJSU Bus. 142 - David Bentley <ul><li>RUMBA is a device used to check the efficacy of the business case </li></ul><ul><ul><li>R ealistic </li></ul></ul><ul><ul><li>U nderstandable </li></ul></ul><ul><ul><li>M easurable </li></ul></ul><ul><ul><li>B elievable </li></ul></ul><ul><ul><li>A ctionable </li></ul></ul>
  24. 24. D M AIC Measure – (1) Rev. 11/15/07 SJSU Bus. 142 - David Bentley <ul><li>Two major steps: </li></ul><ul><ul><li>Selecting process outcomes </li></ul></ul><ul><ul><li>Verifying measurements </li></ul></ul>
  25. 25. D M AIC Measure – (2) Rev. 10/29/08 SJSU Bus. 142 - David Bentley <ul><li>Selecting process outcomes (step 1) </li></ul><ul><ul><li>Tools Used: </li></ul></ul><ul><ul><ul><li>Process map (flowchart) </li></ul></ul></ul><ul><ul><ul><li>XY matrix (like QFD) </li></ul></ul></ul><ul><ul><ul><li>FMEA (Failure Modes and Effects Analysis) </li></ul></ul></ul><ul><ul><ul><li>(aka DFMEA) </li></ul></ul></ul><ul><ul><ul><li>Gauge R&R (Repeatability and Reproducibility) </li></ul></ul></ul><ul><ul><ul><li>Capability Assessment (c p or c pk ) </li></ul></ul></ul>
  26. 26. D M AIC Measure – (3) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Verifying measurements (step 2) </li></ul><ul><ul><li>Tools Used: </li></ul></ul><ul><ul><ul><li>Gauges, calipers and other tools. </li></ul></ul></ul><ul><ul><ul><li>Management System Analysis (MSA) is used to determine if measurements are consistent </li></ul></ul></ul>
  27. 27. D M AIC Measure – (4) 11/13/07 SJSU Bus. 142 - David Bentley <ul><ul><li>Gauge R&R </li></ul></ul><ul><ul><ul><li>Most commonly used MSA </li></ul></ul></ul><ul><ul><ul><li>Determine the accuracy and precision of your measurements </li></ul></ul></ul>
  28. 28. D M AIC Repeatability & Reproducibility 11/13/07 SJSU Bus. 142 - David Bentley
  29. 29. Measurement System D M AIC Evaluation <ul><li>Variation can be due to: </li></ul><ul><ul><li>Process variation </li></ul></ul><ul><ul><li>Measurement system error </li></ul></ul><ul><ul><ul><li>Random </li></ul></ul></ul><ul><ul><ul><li>Systematic ( bias ) </li></ul></ul></ul><ul><ul><li>A combination of the two </li></ul></ul>02/26/06 SJSU Bus. 142 - David Bentley
  30. 30. D M AIC Metrology - 1 <ul><li>Definition: The Science of Measurement </li></ul><ul><li>Accuracy </li></ul><ul><ul><li>How close an observation is to a standard </li></ul></ul><ul><li>Precision </li></ul><ul><ul><li>How close random individual measurements are to each other </li></ul></ul>02/26/06 SJSU Bus. 142 - David Bentley
  31. 31. D M AIC Metrology - 2 <ul><li>Repeatability </li></ul><ul><ul><li>Instrument variation </li></ul></ul><ul><ul><li>Variation in measurements using same instrument and same individual </li></ul></ul><ul><li>Reproducibility </li></ul><ul><ul><li>Operator variation </li></ul></ul><ul><ul><li>Variation in measurements using same instrument and different individual </li></ul></ul>02/26/06 SJSU Bus. 142 - David Bentley
  32. 32. D M AIC R&R Studies <ul><li>Select m operators and n parts </li></ul><ul><li>Calibrate the measuring instrument </li></ul><ul><li>Randomly measure each part by each operator for r trials </li></ul><ul><li>Compute key statistics to quantify repeatability and reproducibility </li></ul>02/26/06 SJSU Bus. 142 - David Bentley
  33. 33. D M AIC R&R Spreadsheet Template 02/25/06 SJSU Bus. 142 - David Bentley
  34. 34. D M AIC R&R Evaluation <ul><li>Repeatability and/or reproducibility error as a percent of the tolerance </li></ul><ul><ul><li>Acceptable: < 10% </li></ul></ul><ul><ul><li>Unacceptable: > 30% </li></ul></ul><ul><ul><li>Questionable: 10-30% </li></ul></ul><ul><ul><ul><li>Decision based on criticality of the quality characteristic being measured and cost factors </li></ul></ul></ul>Rev. 11/27/06 SJSU Bus. 142 - David Bentley
  35. 35. D M AIC Calibration <ul><li>Compare 2 instruments or systems </li></ul><ul><ul><li>1 with known relationship to national standards </li></ul></ul><ul><ul><li>1 with unknown relationship to national standards </li></ul></ul>02/26/06 SJSU Bus. 142 - David Bentley
  36. 36. DM A IC Analyze – (1) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Three major steps: </li></ul><ul><ul><li>Define your performance objectives ( X ’ s ) </li></ul></ul><ul><ul><li>Identify independent variables </li></ul></ul><ul><ul><li>Analyze sources of variability </li></ul></ul>
  37. 37. DM A IC Analyze – (2) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Define your performance objectives ( X ’ s) (step 1) </li></ul>
  38. 38. DM A IC Analyze – (3) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Identify the independent variables where data will be gathered (step 2) </li></ul><ul><ul><li>Process maps (flowcharts), XY matrices , brainstorming, and FMEA ’ s are the tools used </li></ul></ul>
  39. 39. DM A IC Analyze – (4) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Analyze sources of variability (step 3) </li></ul><ul><ul><li>Use visual and statistical tools to better understand the relationships between dependent and independent variables </li></ul></ul>
  40. 40. DMA I C Improve Rev. 11/03/08 SJSU Bus. 142 - David Bentley <ul><li>Off-line experimentation </li></ul><ul><ul><li>Analysis of variance (ANOVA) </li></ul></ul><ul><ul><ul><li>Determines whether independent variable affect variation in dependent variables </li></ul></ul></ul><ul><ul><li>Taguchi method or approach </li></ul></ul>
  41. 41. DMAI C Control Phase Rev. 10/29/08 SJSU Bus. 142 - David Bentley <ul><li>Manage the improved processes using control charts … covered in: </li></ul><ul><ul><li>Variables </li></ul></ul><ul><ul><li>Attributes </li></ul></ul>
  42. 42. The Taguchi Method 11/13/07 SJSU Bus. 142 - David Bentley
  43. 43. The Taguchi Method provides: Rev. 04/28/08 SJSU Bus. 142 - David Bentley <ul><li>A basis for determining the functional relationship between controllable factors </li></ul><ul><li>A method for adjusting a mean of a process by optimizing controllable variables. </li></ul><ul><li>A procedure for examining the relationship between random noise … and product or service variability </li></ul>
  44. 44. Design of Experiments (DOE) Rev. 11/03/08 SJSU Bus. 142 - David Bentley <ul><li>Robust design – designed so that products are inherently defect free </li></ul><ul><li>Concept Design – considers process design and technology choices </li></ul><ul><li>Parameter Design – selection of control factors and optimal levels </li></ul><ul><li>Tolerance Design – specification limits </li></ul>
  45. 45. The Taguchi Process 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Problem identification </li></ul><ul><li>Brainstorming session </li></ul><ul><li>Experimental design </li></ul><ul><li>Experimentation </li></ul><ul><li>Analysis </li></ul><ul><li>Confirming experiment </li></ul>
  46. 46. Taguchi Quality Loss Function <ul><li>Traditional view: anything within specification limits is OK, with no loss </li></ul><ul><li>Taguchi </li></ul><ul><ul><li>Any variation from the target mean represents a potential loss </li></ul></ul><ul><ul><li>The greater the distance from the target mean the greater the potential loss </li></ul></ul>04/28/08 SJSU Bus. 142 - David Bentley
  47. 47. Design for Six Sigma DFSS 11/13/07 SJSU Bus. 142 - David Bentley
  48. 48. Design for Six-Sigma (DFSS) Rev. 11/03/08 SJSU Bus. 142 - David Bentley <ul><li>Used in designing new products with high performance, instead of DMAIC </li></ul><ul><ul><li>DMADV (see next slide) </li></ul></ul><ul><ul><li>IDOV (see 2 slides ahead) </li></ul></ul><ul><li>Focuses on final engineering design optimization </li></ul><ul><li>Relates to new processes and products </li></ul>
  49. 49. DMADV 11/13/07 SJSU Bus. 142 - David Bentley <ul><ul><li>Design </li></ul></ul><ul><ul><li>Measure </li></ul></ul><ul><ul><li>Analyze </li></ul></ul><ul><ul><li>Design </li></ul></ul><ul><ul><li>Verify </li></ul></ul>
  50. 50. IDOV 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Identify </li></ul><ul><li>Design </li></ul><ul><li>Optimize </li></ul><ul><li>Verify </li></ul>
  51. 51. Reasons for Six Sigma Failure 11/13/07 SJSU Bus. 142 - David Bentley
  52. 52. Reasons for Six-Sigma Failure - (1) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Lack of leadership by champions </li></ul><ul><li>Misunderstood roles and responsibility </li></ul><ul><li>Lack of appropriate culture for improvement </li></ul>
  53. 53. Reasons for Six-Sigma Failure - (2) 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>Resistance to change and the Six-Sigma structure </li></ul><ul><li>Faulty strategies for deployment </li></ul><ul><li>Lack of data </li></ul>
  54. 54. Summary 11/13/07 SJSU Bus. 142 - David Bentley <ul><li>The process for Six-Sigma is define, measure, analyze, improve and control </li></ul><ul><li>Keys to Six-Sigma success are skilled management, leadership and long-term commitment </li></ul>

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