Lecture 11 - Six-Sigma Management and Tools

1. Lecture 11 - Six-Sigma Management and Tools 6Σ Organization, DMAIC, Taguchi Method, Robust Design, Design of Experiments, Design for Six Sigma, Reasons for 6Σ Failure SJSU Bus. 142 - David Bentley

2. Topics SJSU Bus. 142 - David Bentley

3. Six Sigma Evolution • Started as a simple quality metric at Motorola in 1986 (Bill Smith) • Concept migrated to Allied Signal • (acquired Honeywell and took its name) • Picked up by General Electric • Commitment by CEO Jack Welch in 1995 • Grown to be an integrated strategy for attaining extremely high levels of quality SJSU Bus. 142 - David Bentley

4. What is Six-Sigma? SJSU Bus. 142 - David Bentley

5. Percent Not Meeting Specifications • +1Σ = 32% • +2Σ = 4.5% • +3Σ = 0.3% • +6Σ = 0.00034% SJSU Bus. 142 - David Bentley

6. Six-Sigma Levels SJSU Bus. 142 - David Bentley

7. Statistics - DPU • Defect • Six Sigma: “any mistake or error passed on to the customer” ??? • General view: any variation from specifications • DPU (defects per unit) • Number of defects per unit of work • Ex: 3 lost bags ÷ 8,000 customers = .000375 SJSU Bus. 142 - David Bentley

8. Statistics – dpmo (defects per million opportunities) • Process may have more than one opportunity for error (e.g., airline baggage) • dpmo = (DPU× 1,000,000) ÷ opportunities for error • Ex: (.000375)(1,000,000) ÷ 1.6 = 234.375 or (3 lost bags × 1,000,000) ÷ (8,000 customers × 1.6 average bags) = 234.375 SJSU Bus. 142 - David Bentley

9. Statistics – dpmo (cont’d) • May extend the concept to include higher level processes • E.g., may consider all opportunities for errors for a flight (from ticketing to baggage claim) SJSU Bus. 142 - David Bentley

10. Statistics - Off-Centering • Represents a shift in the process mean • Impossible to always keep the process mean the same (this WOULD be perfection) • Does NOT represent a change in specifications • Control of shift within ± 1.5 σ of the target mean keeps defects to a maximum of 3.4 per million SJSU Bus. 142 - David Bentley

11. Statistics - Off-Centering (cont’d)Source: Evans & Lindsay, The Management and Control of Quality, Southwestern, 2005 SJSU Bus. 142 - David Bentley

12. k-Sigma Quality Levels • Number of defects per million opportunities • For a specified off-centering and • a desired quality level SJSU Bus. 142 - David Bentley

13. k-Sigma Quality Levels Source: Evans & Lindsay, The Management and Control of Quality, Southwestern, 2005 SJSU Bus. 142 - David Bentley

14. Six Sigma and Other Techniques SJSU Bus. 142 - David Bentley

15. Organizing Six Sigma SJSU Bus. 142 - David Bentley

16. Key Players SJSU Bus. 142 - David Bentley

17. Distribution of Six Sigma Trained Employees SJSU Bus. 142 - David Bentley

18. Six Sigma Tools DMAIC, Taguchi Method, Design for Six Sigma SJSU Bus. 142 - David Bentley

19. DMAIC SJSU Bus. 142 - David Bentley

20. DMAICDMAIC Overview SJSU Bus. 142 - David Bentley

21. DMAICDefine – (1) SJSU Bus. 142 - David Bentley

22. DMAICDefine – (2) SJSU Bus. 142 - David Bentley

23. DMAICDefine – (3) SJSU Bus. 142 - David Bentley

24. DMAICMeasure – (1) SJSU Bus. 142 - David Bentley

25. DMAICMeasure – (2) SJSU Bus. 142 - David Bentley

26. DMAICMeasure – (3) SJSU Bus. 142 - David Bentley

27. DMAICMeasure – (4) SJSU Bus. 142 - David Bentley

28. DMAICRepeatability & Reproducibility SJSU Bus. 142 - David Bentley

29. Measurement System DMAIC Evaluation • Variation can be due to: • Process variation • Measurement system error • Random • Systematic (bias) • A combination of the two SJSU Bus. 142 - David Bentley

30. DMAICMetrology - 1 • Definition: The Science of Measurement • Accuracy • How close an observation is to a standard • Precision • How close random individual measurements are to each other SJSU Bus. 142 - David Bentley

31. DMAICMetrology - 2 • Repeatability • Instrument variation • Variation in measurements using same instrument and same individual • Reproducibility • Operator variation • Variation in measurements using sameinstrument and different individual SJSU Bus. 142 - David Bentley

32. DMAICR&R Studies • Select m operators and n parts • Calibrate the measuring instrument • Randomly measure each part by each operator for r trials • Compute key statistics to quantify repeatability and reproducibility SJSU Bus. 142 - David Bentley

33. DMAICR&R Spreadsheet Template SJSU Bus. 142 - David Bentley

34. DMAICR&R Evaluation • Repeatability and/or reproducibility error as a percent of the tolerance • Acceptable: < 10% • Unacceptable: > 30% • Questionable: 10-30% • Decision based on criticality of the quality characteristic being measured and cost factors SJSU Bus. 142 - David Bentley

35. DMAICCalibration • Compare 2 instruments or systems • 1 with known relationship to national standards • 1 with unknown relationship to national standards SJSU Bus. 142 - David Bentley

36. DMAICAnalyze – (1) SJSU Bus. 142 - David Bentley

37. DMAICAnalyze – (2) SJSU Bus. 142 - David Bentley

38. DMAICAnalyze–(3) SJSU Bus. 142 - David Bentley

39. DMAICAnalyze–(4) SJSU Bus. 142 - David Bentley

40. DMAICImprove SJSU Bus. 142 - David Bentley

41. DMAICControl Phase SJSU Bus. 142 - David Bentley

42. The Taguchi Method SJSU Bus. 142 - David Bentley

43. The Taguchi Method provides: SJSU Bus. 142 - David Bentley

44. Design of Experiments (DOE) SJSU Bus. 142 - David Bentley

45. The Taguchi Process SJSU Bus. 142 - David Bentley

46. Taguchi Quality Loss Function • Traditional view: anything within specification limits is OK, with no loss • Taguchi • Any variation from the target mean represents a potential loss • The greater the distance from the target mean the greater the potential loss SJSU Bus. 142 - David Bentley

47. Design for Six Sigma DFSS SJSU Bus. 142 - David Bentley

48. Design for Six-Sigma (DFSS) SJSU Bus. 142 - David Bentley

49. DMADV SJSU Bus. 142 - David Bentley

50. IDOV SJSU Bus. 142 - David Bentley