1. Achieving Customer Defined Quality Amit Deokar M.S. (Industrial Engineering) Systems and Industrial Engineering University of Arizona Tucson, AZ

2. Way to Customer-Defined Quality Conformance/ Non-Conformance Capability Indices Loss

3. Capability Indices Characterizes what a process will produce in future Statistically stable process necessary Natural Process Limits: What the Process will produce Specifications: Minimally acceptable Product

4. Some Capability Indices  : - Juran (1974)  Indicates the “potential” proportion conforming, due to the centering assumption  : - Kane (1986)  Accounts for the lack of centering assumption  Reinforces the description of Cp as the “potential” capability  : - Chen & Spiring (1988) - Hsiang & Taguchi (1985)  Relatively new and still not used very frequently in industry

5. Capability Indices  Statistics that vary over time even though the underlying process does not change  Easy to misinterpret making process monitoring more difficult  Non-Linear Relationship between Capability Indices and Percent Nonconforming  In complex products, combining specifications on various inter- related dimensions/components to get optimal values is difficult

6. Why not Capability Indices?  Goal-Post Loss – “Zero-Defects” Philosophy  No incentive to improve the process  Not inline with the “Lean Manufacturing” methodology  Are we achieving Customer-Defined Quality?

7. Cost of Poor Quality  Failure Costs  Internal Failure Costs (e.g. scrap, rework)  External Failure Costs (e.g. warranty charges)  Appraisal Costs  Prevention Costs Reference: “Juran’s Quality Handbook”: Juran & Godfrey

8. Loss (Quadratic)  “On Target with Min. Variance” concept  Incentive for Continual Improvement  Incorporates Cost of Using Conforming Products

9. Loss (Quadratic)  General Form of Quadratic Loss Function (QLF): : Loss for deviation,, from target  Average Loss in case of QLF: (Independent of the probability distribution of the underlying process)

10. where : process distribution : Loss Function used for the model General Form of Average Loss Expected LossVoice of the Customer Voice of the Process

11. Graphical Representation Figure 1 Figure 2 Reference: “Beyond Capability Confusion”: Donald Wheeler

12. General Class of Loss Functions  Reflected Normal Loss Function (Spiring, 1993)  Modified Reflected Normal Loss Function (Sun, Laramee & Ramberg, 1995)  General Class of Loss Functions (Spiring & Yeung, 1998)

13.  Cpm & Average Quadratic Loss:  Relation to Expected Quadratic Loss: Process Incapability Index (Greenwich (1995))  Another form by Ramberg (2002): Capability Index Motivated by QLF

14. Example in Automotive Transmissions  3 processes – Frictional Clutch Plate Manufacturing  None make more than 0.27% scrap relative to specs  Scraping Cost - $2.50/part Reference: “Taguchi Techniques for Quality Engineering” – Phillip J. Ross

15. Example in Automotive Transmissions Reference: “Taguchi Techniques for Quality Engineering” – Phillip J. Ross

16. What do we learn?  On-Target with reduced variation  Competitive Product with Reduced Loss to Society (Both Producers & Customers)  Missing the target value - a serious loss compared to hitting the target with increased variation  Capability Indices Cp & Cpk - Bottom-Line improvements not motivated (Cpm - motivated by Loss Function concept itself)  Process 2 seems to be expensive for the producers. But, with Loss Function at work, they are actually cheaper

17. Loss Function for Multiple Components For a system of independent components having similar functions Expected Losses due to deviations are given by,

18.  Criteria :  Degree of problem resolution (R)  Length of call time (X)  Incremental Billing Plans  $4 per min  Customer Satisfaction Scores (VOC) Product Sales Example in Tech Support Call Center

19. Call Time Criterion  Loss – Linear  Call Time Distribution – Exponential ~ (20, 25)

20. Problem Resolution Criterion  Loss – Quadratic  Call Resolution Distribution – Discrete

21. Loss Computation  For Call Time length criterion,  For degree of Problem Resolution criterion,

22. Loss Computation  Total Loss =  Average Loss =

23. Conclusions  Conformance to Specifications – Necessary but not sufficient  Capability Indices – Useful but not sufficient  Loss Functions  Focus on reducing the “Loss” to the Society  Incorporate the True Voice of Customer  Helps in designing better products & processes  Need to take research to industry