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Lecture 14A - Managing Supplier Quality in the Supply Chain (Chapter 9)

Lecture 14A - Managing Supplier Quality in the Supply Chain (Chapter 9). Value chains, Supplier partnering and development , ISO/TFS 16949, Acceptance sampling. Topics. The Value Chain. The Chain of Customers. Managing the Supply Chain. Supplier Partnering - (1).

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Lecture 14A - Managing Supplier Quality in the Supply Chain (Chapter 9)

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  1. Lecture 14A -Managing Supplier Quality in the Supply Chain (Chapter 9)

    Value chains, Supplier partnering and development, ISO/TFS 16949, Acceptance sampling SJSU Bus. 142 - David Bentley
  2. Topics SJSU Bus. 142 - David Bentley
  3. The Value Chain SJSU Bus. 142 - David Bentley
  4. The Chain of Customers SJSU Bus. 142 - David Bentley
  5. Managing the Supply Chain SJSU Bus. 142 - David Bentley
  6. Supplier Partnering - (1) SJSU Bus. 142 - David Bentley
  7. Supplier Partnering - (2) SJSU Bus. 142 - David Bentley
  8. Supplier Partnering - (3) SJSU Bus. 142 - David Bentley
  9. Supplier Development SJSU Bus. 142 - David Bentley
  10. Supplier Relationship Management Systems (SRMS) SJSU Bus. 142 - David Bentley
  11. The Contingency Perspective SJSU Bus. 142 - David Bentley
  12. A Supplier Development Program: ISO/TS 16949 SJSU Bus. 142 - David Bentley
  13. ISO/TS 16949 ISO/TS 16949 based on a model: Quality management system Management responsibility Resource management Product realization Measurement, analysis and improvement Closely aligned with ISO 9000:2008 SJSU Bus. 142 - David Bentley
  14. Acceptance Sampling Definition: statistical quality control technique “applied to lots or batches of items before or after a process, to judge conformance with predetermined standards” (from Stephenson) Acceptance sampling is controversial Some believe it to conflict with Deming’s position on continual improvement SJSU Bus. 142 - David Bentley
  15. Acceptance Sampling Form of inspection applied to lots or batches Before or after a process, not during the process Purpose: determine whether lot satisfies predetermined standards SJSU Bus. 142 - David Bentley
  16. Acceptance Sampling SJSU Bus. 142 - David Bentley
  17. Type I and Type II Errors Type I (producer’s risk) Conclusion: non-randomness is present and the process is out of control or the lot is bad Action: stop the process which was OK or reject lot Reality: randomness is present and the process is in control or the lot is OK Type II (consumer’s risk) Conclusion: randomness is present and the process is in control or the lot is OK Action: don’t stop the process; continue making defects or reject lot Reality: non-randomness is present and the process is out of control or the lot is bad SJSU Bus. 142 - David Bentley
  18. Alpha and Beta Risks SJSU Bus. 142 - David Bentley
  19. Acceptance Levels Acceptable Quality Level (AQL) Customers may be willing to accept lots containing less than or equal to a specified % defects Relates to Type I risk (α or Producer’s risk) Lot Tolerance Percent Defective (LTPD) Upperlimit of the percentage of defects actually tolerated in accepted lots Relates to Type II risk (β or Consumer’s risk) SJSU Bus. 142 - David Bentley
  20. Operating characteristic (OC) Curves SJSU Bus. 142 - David Bentley
  21. 1 0.9 0.8 0.7 0.6 Probability of accepting lot 0.5 0.4 0.3 0.2 3% 0.1 0 0 .05 .10 .15 .20 .25 Lot quality (fraction defective) Operating characteristic curveStevenson, William J., Operations Management, 8th Edition (mod. 09/15/04 DAB) Shows probabilities of accepting lots with various defect fractions SJSU Bus. 142 - David Bentley
  22. Sampling Plans Plan defines: Lot size Sample size Number of samples Acceptance/rejection criteria SJSU Bus. 142 - David Bentley
  23. Single-sampling Plans One random sample from each lot Every item in sample inspected and classified: good or bad If number of defectives(bad) > specified limit, lot is rejected SJSU Bus. 142 - David Bentley
  24. Double-sampling Plans Upper and lower defect limits set for each lot Results of initial sample Defectives≤ lower limit: lot accepted Defectives≥ higher limit: lot rejected Defectivesbetween two limits: take 2nd sample If 2nd sample needed, compare number of defectivesfrom both samples to third value If number of defectives(bad) > specified value, lot is rejected SJSU Bus. 142 - David Bentley
  25. Multiple-sampling Plans More than 2 samples 2 limits specified for each sample Cumulative number of defectivescompared to limits for each successive sample Defectives≤ lower limit: lot accepted Defectives≥ higher limit: lot rejected Defectivesbetween two limits: continue sampling SJSU Bus. 142 - David Bentley
  26. Acceptance Sampling in Continuous Production Differs from lot-by-lot sampling Typically alternate between 100% and sampling inspection Described in DOD MIL STD 1235C (1988) SJSU Bus. 142 - David Bentley
  27. Summary SJSU Bus. 142 - David Bentley
  28. Sampling example problems SJSU Bus. 142 - David Bentley
  29. Single Sampling Plan Problem Take one sample Reject if defectives > limit Accept if defectives < limit Problem: sample = 60, limit = 2 Number defective = 3 Action: ? SJSU Bus. 142 - David Bentley
  30. Single Sampling Plan Problem Take one sample Reject if defectives > limit Accept if defectives < limit Problem: sample = 60, limit = 2 Number defective = 1 Action: ? SJSU Bus. 142 - David Bentley
  31. Single Sampling Plan Problem Take one sample Reject if defectives > limit Accept if defectives < limit Problem: sample = 60, limit = 2 Number defective = 2 Action: ? SJSU Bus. 142 - David Bentley
  32. Double Sampling Plan Problem Take one sample Reject if defectives > upper limit Accept if defectives < lower limit Take second sample if between limits Problem: sample 1 = 40, UL= 5, LL = 1 Number defective = 6 Action: ? SJSU Bus. 142 - David Bentley
  33. Double Sampling Plan Problem Take one sample Reject if defectives > upper limit Accept if defectives < lower limit Take second sample if between limits Problem: sample 1 = 40, UL= 5, LL = 1 Number defective = 1 Action: ? SJSU Bus. 142 - David Bentley
  34. Double Sampling Plan Problem Take one sample Reject if defectives > upper limit Accept if defectives < lower limit Take second sample if between limits Problem: sample 1 = 40, UL= 5, LL = 1 Number defective = 3 Action: ? SJSU Bus. 142 - David Bentley
  35. Double Sampling Plan Problem Take second sample Reject if total defectives > new limit Accept if total defectives < new limit Problem: sample 2 = 40, new limit = 6 Number defective = 3 + 4 = 7 Action: ? SJSU Bus. 142 - David Bentley
  36. Double Sampling Plan Problem Take second sample Reject if total defectives > new limit Accept if total defectives < new limit Problem: sample 2 = 40, new limit = 6 Number defective = 3 + 1 = 4 Action: ? SJSU Bus. 142 - David Bentley
  37. Multiple Sampling Plan Problem Take second sample Reject if total defectives > upper limit 2 Accept if total defectives < lower limit 2 Take third sample if between limits Problem: sample 3 = 40, UL3= 8, LL3 = 6 Number defective = 3 + 3 + 3 = 9 Action: ? SJSU Bus. 142 - David Bentley
  38. Multiple Sampling Plan Problem Take second sample Reject if total defectives > upper limit 2 Accept if total defectives < lower limit 2 Take third sample if between limits Problem: sample 3 = 40, UL3= 8, LL3 = 6 Number defective = 3 + 3 + 0 = 6 Action: ? SJSU Bus. 142 - David Bentley
  39. Multiple Sampling Plan Problem Take second sample Reject if total defectives > upper limit 2 Accept if total defectives < lower limit 2 Take third sample if between limits Problem: sample 3 = 40, UL3= 8, LL3 = 6 Number defective = 3 + 3 + 1 = 7 Action: ? SJSU Bus. 142 - David Bentley
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