1 / 18

Production and Operations Management: Manufacturing and Services

Production and Operations Management: Manufacturing and Services. PowerPoint Presentation for Chapter 9 Technical Note - Statistical Quality Control. Chase Aquilano Jacobs. The McGraw-Hill Companies, Inc., 2009 Stephen A. DeLurgio, 2009. Irwin/McGraw-Hill.

laszlo
Download Presentation

Production and Operations Management: Manufacturing and Services

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Production and OperationsManagement:Manufacturing and Services PowerPoint Presentation for Chapter 9 Technical Note - Statistical Quality Control Chase Aquilano Jacobs • The McGraw-Hill Companies, Inc., 2009 • Stephen A. DeLurgio, 2009 Irwin/McGraw-Hill

  2. Chapter 9 Supplement - 2Statistical Quality Control • Process Control Procedures - 1 • Variable data • Attribute data • Process Capability - 2 • Acceptance Sampling - 3 • Operating Characteristic Curve 2

  3. MANY PROCESSES ARE VERY IMPORTANT TO CONTROL ! PROCESS PRINCIPLES ARE NEARLY UNIVERSAL LET’S CONSIDER TWO IN CONTROL PACKAGING PROCESSES - B & G THEY PRODUCE AND PACKAGE 10 OZ. PRODUCTS DEVIATIONS FROM THIS 10 OZ. ARE COSTLY.

  4. CONSIDER PROCESS B - BADMEAN WT. = 10 OZ., STD DEV=.210,000 PRODUCED 10 +/- .2 68% 6,800 OF 10,000 IN THIS RANGE 10 +/- .4 95% 9,500 OF 10,000 IN THIS RANGE 10 +/- .6 99.73% 9,973 OF 10,000 IN THIS RANGE 10 +/- .8 99.994% 9,999.4 OF 10,000 IN THIS RANGE

  5. CONSIDER PROCESS G - GOODMEAN WT. = 10 OZ., STD DEV=.0510,000 PRODUCED 10 +/- .05 68% 6,800 OF 10,000 IN THIS RANGE 10 +/- .10 95% 9,500 OF 10,000 IN THIS RANGE 10 +/- .15 99.73% 9,973 OF 10,000 IN THIS RANGE 10 +/- .20 99.994% 9,999.4 OF 10,000 IN THIS RANGE

  6. PROCESS B HAS FOUR TIMES THE VARIATION OF G PROCESS B, STD. DEV. = .20 PROCESS G, STD. DEV. = .05

  7. ARE THESE GOOD OR DEFECTIVE PRODUCTS? ULTIMATELY EITHER THE CUSTOMERS OR THE GOV’T DECIDES OR MAY BE THE COMPETITION! AFTER SOMEONE DECIDES, THEN WE SHOULD COMPAREGOOD OR DEFECTIVE WITH PROCESS VARIATION! WE CAN DETERMINE WHETHER THE PROCESS IS CAPABLE OR NOT CAPABLE AFTER SPECS ARE DEFINED, IT NOT CAPABLE, THEN CHANGE PROCESS OR SPECS.! GOOD OR DEFECTIVEOUTPUT IS DECIDED BY SPECIFICATION LIMITS.

  8. GOOD AND DEFECTIVE PRODUCTS: UPPER SPECIFICATION LEVEL = 10.20 OZ. LOWER SPECIFICATION LEVEL = 9.80 OZ. ABOVE USL = DEFECTIVE PRODUCT! BELOW LSL = DEFECTIVE PRODUCT! BETWEEN LSL AND USL = GOOD PRODUCT WHICH OF THE TWO PROCESSES, B OR G IS MORE CAPABLE OF MEETING SPECS? PRO. B: MEAN WT. = 10 OZ., STD DEV=.2 PRO. G: MEAN WT. = 10 OZ., STD DEV=.05

  9. GOOD AND DEFECTIVE PRODUCTS CAPABLE OR INCAPABLE PROCESSES: FROM 9.80 OZ. TO 10.20 OZ. IS A GOOD PRODUCT FROM LSL TO USL IS A GOOD PRODUCT PRO. B: MEAN = 10 STD DEV=.2 9.80 TO 10.20 IS +/- 1 STD DEV FOR PROCESS B 68% 9.80 TO 10.20 THUS 32% DEFECTIVE PRO. G: MEAN = 10 STD DEV=.05 9.80 TO 10.20 IS +/- 4 STD DEV. FOR PROCESS G 99.994% 9.80 TO 10.20 THUS .006% DEFECTIVE THIS IS ONLY 6 OUT OF 100,000 PRODUCTS CLEARLY PROCESS G IS MORE CAPABLE !!!!

  10. “B” HAS 4x THE VARIATION OF “G” B, STD. DEV. = .20 G, STD. DEV. = .05 Cpk=MIN[(USL-m)/3S, (MEAN-m)/3S] LSL USL

  11. NOW 6 DEFECTIVE OUT OF 100,000 MAY BE TOO MANY! WHAT CAN BE DONE ABOUT THIS? CHANGE THE SPECS. OR CHANGE THE PROCESS VARIATION! ALMOST ALWAYS THE PROCESS SHOULD BE CHANGED.

  12. OTHER ND INTERVALS MEAN +/- ONE STANDARD DEVIATION 68% MEAN +/- 1.96 STANDAR DEVIATRIONS 95% MEAN +/- 3.00 STANDARD DEVIATIONS 99.73% MEAN +/- 4.00 STANDARD DEVIATIONS 99.994% MEAN +/- 5.00 STANDARD DEVIATIONS 99.99994% MEAN +/- 6.00 STANDARD DEVIATIONS 99.99999%

  13. THE SMALLER THE VARIATION THE MORE CAPABLE THE PROCESS A CAPABLE PROCESS HAS 8*STD. DEV.  USL - LSL = SPEC. RANGE CONSIDER PROCESS “G” 8*STD. DEV = 8*.05 = .40  10.20 - 8.80 = .40 THESE ASSUME THE PROCESS MEAN IS CENTERED ON SPEC. RANGE

  14. IS PROCESS “B” A CAPABLE PROCESS ? A CAPABLE PROCESS HAS 8*STD. DEV.  USL - LSL = SPEC. RANGE CONSIDER PROCESS “B” 8*STD. DEV = 8*.20 = 1.60 > > .40 THIS PROCESS IS NOT CAPABLE IT WILL PRODUCE MANY DEFECTS NO MATTER WHAT WE DO!!!

  15. GENERALLY THE OUTPUT IS NOT CENTERED ON SPEC. LIMITS BOTH SPEC LIMITS MUST BE AT LEAST 4 SIGMA AWAY FROM THE MEAN TO HAVE A CAPABLE PROCESS. THIS PROVIDES A SIMPLE COOKBOOK FORMULA TO DETERMINE IF A PROCESS IS CAPABLE. THIS FORMULA IS CALLED Cpk - PROCESS CAPABILITY INDEX

  16. PROCESS CAPABILITY INDEX - Cpk THE PROCESS CAPABILITY IS MEASURED USING AN INDEX: Cpk = MIN[(USL-MEAN)/3S,(MEAN-LSL)/3S] Cpk = MIN[(10.20-10)/3*.05,(10-9.80)/3*.05)] Cpk = MIN[(1.33,1.33)] = 1.33 A CAPABLE PROCESS HAS A Cpk  1.33 The larger the better!

  17. Process Capability • Process Variation +/- 3 Sigma • Tolerance/Specification Limits LSL to USL • How do the limits relate to one another? • There is no theoretical link, only our need to make +/- 4 Sigma <<< USL-LSLS 28

  18. High High Incremental Cost of Variability Incremental Cost of Variability Zero Zero Lower Spec Target Spec Upper Spec Lower Spec Target Spec Upper Spec Traditional View Taguchi’s View Taguchi’s View of Variation 30

More Related