Achieving Customer Defined Quality Amit Deokar M.S. (Industrial Engineering) Systems and Industrial Engineering University of Arizona Tucson, AZ
Way to Customer-Defined Quality Conformance/ Non-Conformance Capability Indices Loss
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
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
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
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?
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
Loss (Quadratic) “On Target with Min. Variance” concept Incentive for Continual Improvement Incorporates Cost of Using Conforming Products
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)
where : process distribution : Loss Function used for the model General Form of Average Loss Expected LossVoice of the Customer Voice of the Process
Graphical Representation Figure 1 Figure 2 Reference: “Beyond Capability Confusion”: Donald Wheeler
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)
Cpm & Average Quadratic Loss: Relation to Expected Quadratic Loss: Process Incapability Index (Greenwich (1995)) Another form by Ramberg (2002): Capability Index Motivated by QLF
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
Example in Automotive Transmissions Reference: “Taguchi Techniques for Quality Engineering” – Phillip J. Ross
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
Loss Function for Multiple Components For a system of independent components having similar functions Expected Losses due to deviations are given by,
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
Call Time Criterion Loss – Linear Call Time Distribution – Exponential ~ (20, 25)
Problem Resolution Criterion Loss – Quadratic Call Resolution Distribution – Discrete
Loss Computation For Call Time length criterion, For degree of Problem Resolution criterion,
Loss Computation Total Loss = Average Loss =
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