Asq Auto Webinar Spc Common Questions Web

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Asq Auto Webinar Spc Common Questions Web

  1. 1. ASQ Automotive Division Webinar Series SPC Some common questions May 27 8PM EDT Presenter: John Katona
  2. 2. ASQ Automotive Division Webinar Series SPC Some common questions May 27 8PM EDT Agenda : 5 Min Introduction 70 Min presentation 10 Min Q&A
  3. 3. ASQ Automotive Division ASQ Automotive Division is part of the American Society for Quality (ASQ), the world’s leading authority on quality issues since 1946. ASQ Automotive Division has more than 3400 members globally. Members include professionals from almost every discipline in the vehicle manufacturing and supplier business in the automotive, heavy-truck, off-highway, agricultural, industrial and construction equipment industries.
  4. 4. ASQ Automotive Division <ul><li>VISION </li></ul><ul><ul><li>To be the worldwide leader on quality issues related to the automotive industry. </li></ul></ul><ul><li>MISSION </li></ul><ul><ul><li>To provide member value by identifying, communicating, and promoting quality knowledge, professional development and networking opportunities. </li></ul></ul>
  5. 5. ASQ Automotive Division <ul><li>OBJECTIVES: </li></ul><ul><ul><li>Be a global provider of automotive quality knowledge and learning opportunities for advancing individual and organizational performance excellence. </li></ul></ul><ul><ul><li>Engage, grow and retain members through new and improved communities and cutting-edge technologies. </li></ul></ul><ul><ul><li>Develop and sustain a strong Council Leadership to support our members. </li></ul></ul>
  6. 6. Statistical Process Control Some Common Questions John Katona Secretary ASQ Automotive Division
  7. 7. Question 1 My process has several sources of variation: Can I put them all on (1) chart? Can I put all (12) nests on the same chart or do I need (12) charts? My mold makes (32) parts in every shot. Can I just grab any (4) parts from a shot and maintain only a single chart?
  8. 9. Can I put all (5) of these spindles on the same chart?
  9. 10. Can I put all (5) of these spindles on the same chart? Yes – they all have about the same average & spread.
  10. 11. Each Subgroup contains all (5) Spindles – Data is from (5) identical distributions, all normal with mean 30 and standard deviation 0.7
  11. 12. Each Subgroup contains only (1) Spindle – Data is from (5) identical distributions, all normal with mean 30 and standard deviation 0.7
  12. 13. Can I put all (5) of these fixtures on the same chart?
  13. 14. Can I put all (5) of these fixtures on the same chart? NO – they have averages that are very different.
  14. 15. Each Subgroup contains all (5) Fixtures – When it looks too good to be true, it is too good to be true
  15. 16. Each Subgroup contains all (5) Fixtures – When it looks too good to be true, it is too good to be true
  16. 17. Each Subgroup contains only (1) Fixture – The averages for each fixture are very different
  17. 18. Each Subgroup contains only (1) Fixture – The averages for each fixture are very different
  18. 19. Question 1 My process has several sources of variation: Can I put them all on (1) chart? Can I put all (12) nests on the same chart or do I need (12) charts? Do all (12) nests have the same average & spread? My mold makes (32) parts in every shot. Can I just grab any (4) parts from a shot and maintain only a single chart? Do all (32) cavities have the same average & spread? Answer: If the averages and spreads are the same, then yes. Otherwise NO.
  19. 20. I have an engineering specification. Why do I need statistical control limits? Can’t I just put the spec or 70% of the spec on the control chart? Question 2
  20. 21. Critical Distinctions <ul><li>Specifications apply to the parts . </li></ul><ul><li>Specifications tell if a part meets customer requirements </li></ul><ul><li>Specifications do not apply to the process that makes the parts. Specifications do not tell if the process has changed . </li></ul><ul><li>A process where all parts are within specifications may or may not be “In Control” (Predictable) </li></ul><ul><li>Control limits apply to the process that makes the parts. </li></ul><ul><li>Control limits do not tell if the parts meet customer requirements. </li></ul><ul><li>Control Limits tell when the process has changed . </li></ul><ul><li>A process that is “In Control” is predictable . </li></ul><ul><li>A process that is “In Control” may or may not be making parts within specifications </li></ul>
  21. 22. Is this process “In control” or “predictable”?
  22. 23. Is this process “In control” or “predictable”? The Specifications and distribution shape don’t reveal anything about process stability or predictability from one time period to the next. Is this process Changing from (1) time period to the next? Without the control chart you don’t know.
  23. 24. Is this process “predictable”?
  24. 25. Is this process “predictable”? It looks pretty predictable.
  25. 26. Are these parts “in Specification”?
  26. 27. Are these parts “in Specification”? The Control Chart does not answer this question!
  27. 28. Question2 I have an engineering specification. Why do I need statistical control limits? 1. Engineering spec. is for classifying parts as conforming or non conforming to Customer Requirement, it does not signal process change. 2. Control limits signal process change. They do not classify parts as meeting Customer Requirements.
  28. 29. I’m measuring “flatness” or “leak” or “roundness”. Why do I have a Lower Control Limit? Shouldn’t it just be 0?
  29. 30. I’m measuring “flatness” or “leak” or “roundness”. Why do I have a Lower Control Limit? Shouldn’t it just be 0? This point is below the Lower Control Limit. This is unusual compared to where the process ordinarily makes product. Control Limits alert us to process changes and unusual events
  30. 31. I’m measuring “Weld Strength”. Why do I have an Upper Control Limit?
  31. 32. I’m measuring “Weld Strength”. Why do I have an Upper Control Limit? These point are above the Upper Control Limit. This is unusual compared to where the process ordinarily makes product. Control Limits alert us to process changes and unusual events
  32. 33. Why are my control limits so narrow? Why would we control the process tighter than the specification?? Subgroup Size n=1
  33. 34. Why are my control limits so narrow? Why would we control the process tighter than the specification?? Subgroup Size n=1 Control limits tell us where the process ordinarily makes product. Control limits are based on data from the process, not on the specification. Control Limits alert us to process changes and unusual events. A process that is very “Capable” will have control limits narrower than the specification.
  34. 35. Why are my control limits so narrow? Why would we control the process tighter than the specification?? Subgroup Size n=5 Control limits tell us where the process ordinarily makes product. Control limits are based on data from the process, not on the specification. Control Limits alert us to process changes and unusual events. A process that is very “Capable” will have control limits narrower than the specification. Increasing the Subgroup Size will further “tighten” the control limits.
  35. 36. Why are my control limits so wide? We are allowing the process to vary way beyond the specifications! Subgroup Size n=1
  36. 37. Why are my control limits so wide? We are allowing the process to vary way beyond the specifications! Subgroup Size n=1 Control limits tell us where the process ordinarily makes product. Control limits are based on data from the process, not on the specification. Control Limits alert us to process changes and unusual events. A process that is NOT “Capable” may have control limits wider than the specification. This depends on Subgroup Size. With n=1, here the Control Limits are wider than the specification.
  37. 38. Why are my control limits so wide? We are allowing the process to vary way beyond the specifications! Subgroup Size n=5 Control limits tell us where the process ordinarily makes product. Control limits are based on data from the process, not on the specification. Control Limits alert us to process changes and unusual events. A process that is NOT “Capable” may have control limits wider than the specification. This depends on Subgroup Size. With n=5, the Control Limits are tighter than using n=1, but still wider than the Specification. Notice, that the process is still not “Capable”
  38. 39. Question 3 Cp, Cpk, Pp, Ppk??? What’s all this alphabet soup about? Why are there (4) of these indices??
  39. 40. Cp Cpk Ppk Pp Process CAPABILITY (adjusted for targeting) Cpk can improve to Cp if I can adjust my process average so it is in the middle of the specifications. Process PERFORMANCE (adjusted for targeting) Ppk can improve to Pp if I can adjust my process average so it is in the middle of the specifications.
  40. 41. Cp Cpk Ppk Pp Process PERFORMANCE Pp can improve to Cp if I can stabilize my process on the Control Chart. (Even if I don’t re-target to the middle of the specifications.) Process PERFORMANCE (adjusted for targeting) Ppk can improve to Cpk if I can stabilize my process on the Control Chart. (Even if I don’t re-target to the middle of the specifications.)
  41. 42. Cp Ppk Process PERFORMANCE (adjusted for “targeting) Ppk can improve to Cp if I can stabilize my process on the Control Chart and also re-target to the middle of the specifications.
  42. 43. Content Application Variation within subgroups only Variation both within & between subgroups 1. Short Term Capability 2. Diagnostic use 1. Predicted Performance  d2 = /d 2  n  = i=1 n  (x i -X) 2 n-1
  43. 44. Cp= Total Tolerance  d2 Cpk= The minimum of either 3  d2 or - Lower Specification 3  d2 Upper Specification - X X Capability Indices – Include Within Group Variation Only Cpk will be worse than Cp if the process is not centered within the specifications. “ Cpk shows how good Ppk could be if the process was just stable on the control chart” “ Cp shows how good Ppk could be if the process were targeted within the specifications and stable on the control chart”
  44. 45. Ppk= The minimum of either 3 or - Lower Specification 3 Upper Specification - X X Performance Indices – Include Both Within Group & Between Group Variation  n   n  Pp will be worse than Cp if the process is unstable on the control chart “ Pp shows how good Ppk could be if the process was just targeted within the specifications.” Pp= Total Tolerance  n 
  45. 46. Cp, Cpk, Pp, and Ppk are all virtually equal. How can that be?
  46. 47. Process average is targeted very close to the center of the specifications & points on both X-bar and Range charts indicate decent process stability. Note that Cp, Cpk, Pp, and Ppk are all virtually equal.
  47. 48. Process average is off-target from the center of the specifications & points on both X-bar and Range charts indicate decent process stability. Note that Cp & Pp are virtually equal as are Cpk & Ppk; however Cpk & Ppk are degraded from Cp & Pp as the process is off-target..
  48. 49. Question: Is this process “capable.”
  49. 50. Question: Is this process “capable.” Yes it is “capable”, but not “performing”
  50. 51. Process average is targeted at the center of the specifications so Cp=Cpk & Pp=Ppk. However the X-bar chart is very unstable, so Pp<Cp and Ppk<Cpk.
  51. 52. ASQ Automotive Division Q & A Please type your questions in the chat room
  52. 53. ASQ Automotive Division Webinar Series Thank you for attending the Webinar For video from this webinar please check our website: Video will be delayed by a few weeks: www.asq-auto.org Twitter: @ASQautomotive Facebook: ASQ Automotive division Slides are posted at: http://www.slideshare.net/oldeck Questions & Comments: waltoldeck@gmail.com New Website

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