MINIMIZING MANUFACTURING AND QUALITY COSTS IN MULTIRESPONSE OPTIMIZATION

References

• Lind , E. E. , Goldin , J. , and Hickman , J. B. , Fitting Yield and Cost Response Surfaces , Chem. Eng. Prog ., 56 , 62 – 68 ( 1960 ).
   Google Scholar
• Myers , R. H. and Carter , W. H. , Response Surface Techniques for Dual Response Surfaces , Technometrics , 15 , 301 – 317 ( 1973 ).
   Web of Science ®Google Scholar
• Biles , W. E. , A Response Surface Method for Experimental Optimization of Multircsponse Processes , Ind. Eng. Chem., Process Des. Dev ., 14 , 152 – 158 ( 1975 ).
   Web of Science ®Google Scholar
• Myers , R. H. , Khuri , A. I. , and Vining , G. , Response Surface Alternatives to the Taguchi Robust Parameter Design Approach , Am. Statistician , 46 ( 2 ), 131 – 139 ( 1992 ).
   Web of Science ®Google Scholar
• Myers , R. H. , Montgomery , D. C. , Response Surface Methodology , John Wiley & Sons , New York , 1995 .
   Google Scholar
• Del Castillo , E. , Multiresponse Process Optimization via Constrained Confidence Regions , J. Qual. Technol ., 28 ( 1 ), 61 – 70 ( 1996 ).
   Web of Science ®Google Scholar
• Kim , K. and Lin , D. K. J. , Dual Response Surface Optimization A Fuzzy Modeling Approach , J. Qual. Technol , 30 ( 1 ), 1 – 10 ( 1998 ).
   Web of Science ®Google Scholar
• Harrington , E. C. , Jr. , The Desirability Function , Ind. Qual. Control , 21 ( 10 ), 494 – 498 ( 1965 ).
   Google Scholar
• Derringer , G. and Suich , R. , Simultaneous Optimization of Several Response Variables , J. Qual. Technol ., 12 ( 4 ), 214 – 219 ( 1980 ).
   Web of Science ®Google Scholar
• Chang , S. and Shivpuri , R. , A Multiple-Objective Decision-Making Approach for Assessing Simultaneous Improvement in Die Life and Casting Quality in a Die Casting Process , Qual. Eng ., 7 , 371 – 383 ( 1994 ).
   Google Scholar
• Del Castillo , E. , Montgomery , D. C. , and McCarville , D. R. , Modified Desirability Functions for Multiple Response Optimization , J. Qual. Technol , 28 ( 3 ), 337 – 345 ( 1996 ).
   Web of Science ®Google Scholar
• Fogliatto , F. S. , Albin , S. L. , and Tepper , B. J. , A Hierarchical Approach to Optimizing Descriptive Analysis Multiresponse Experiments , J. Sensory Studies , 14 ( 4 ), 443 – 465 ( 1999 ).
   Web of Science ®Google Scholar
• Khuri , A. I. and Conlon , M. , Simultaneous Optimization of Multiple Responses Represented by Polynomial Regression Functions , Technometrics , 23 ( 4 ), 363 – 375 ( 1981 ).
   Web of Science ®Google Scholar
• Leon , R. V. , Shoemaker , A. C. , and Kacker , R. N. , Performance Measures Independent of Adjustment-An Explanation and Extension of Taguchi's Signal-to-Noise Ratios , Technometrics , 29 ( 3 ), 253 – 265 ( 1987 ).
   Web of Science ®Google Scholar
• Logothetis , N. and Haigh , A. , Characterizing and Optimizing Multircsponse Processes by the Taguchi Method, Qual. Reliab. Eng. Int ., 4, 159–169 (1988).
   Google Scholar
• Tribus , M. and Szonyl , G. , An Alternative View of the Taguchi Approach , Qual. Prog ., 22 , 46 – 52 ( 1989 ).
   Google Scholar
• Yum , B. and Ko , S. , On Parameter Design Optimization Procedures , Qual. Reliab. Eng. Int ., 7 , 39 – 46 ( 1991 ).
   Google Scholar
• Raiman , L. B. and Case , K. E. , The Development and Implementation of Multivariate Cost of Poor Quality Loss Function , IMSE Working Paper 92–52 , Penn State University ( 1992 ).
   Google Scholar
• Elsaycd , E. A. and Chen , A. , Optimal Levels of Process Parameters for Products with Multiple Characteristics , Int. J. Product. Res ., 31 ( 5 ), 1117 – 1132 ( 1993 ).
   Google Scholar
• Pignatiello , J. J. , Jr. , Strategies for Robust Multiresponsc Quality Engineering , IIE Trans ., 25 , 5 – 15 ( 1993 ).
   Web of Science ®Google Scholar
• Ribeiro , J. L. and Elsayed , E. A. , A Case Study on Process Optimization Using the Gradient Loss Function , Int. J. Product. Res ., 33 ( 12 ), 3233 – 3248 ( 1995 ).
   Web of Science ®Google Scholar
• Leon , N. A. , A Pragmatic Approach to Multiresponse Problems Using Loss Functions , Qual. Eng ., 9 , 213 – 220 ( 1996 ).
   Google Scholar
• Vining , G. G. , A Compromise Approach to Multiresponse Optimization , J Qual. Technol ., 30 ( 4 ), 309 – 313 ( 1998 ).
   Web of Science ®Google Scholar
• Bartlett , M. S. and Kendall , D. J. , The Statistical Analysis of Variance-Heterogeneity and the Logarithmic Transformation , J. Roy. Statist. Soc. Ser. B , 8 , 128 – 138 ( 1946 ).
   Google Scholar
• Myers , R. H. , Montgomery , D. C. , Response Surface Methodology Process and Product Optimization Using Designed Experiments , John Wiley & Sons , New York , 1995 .
   Google Scholar
• Harvey , A. C . , Estimating Regression Models with Multiplicative Heteroscedascity , Econometrica , 44 ( 3 ), 461 – 465 ( 1976 ).
   Web of Science ®Google Scholar
• Carroll , R. J. and Ruppert , D. Transformation and Weighting in Regression , Chapman & Hall , New York , 1988 .
   Google Scholar
• Shoemaker , A. C. , Tsui , K. L. , and Wu , C. F. J. , Economical Experimentation Methods for Robust Design , Technometrics , 33 ( 4 ), 415 – 427 ( 1991 ).
   Web of Science ®Google Scholar
• Lucas , J. M. , How to Achieve a Robust Process Using Response Surface Methodology , J. Qual. Technol , 26 ( 4 ), 248 – 260 ( 1994 ).
   Web of Science ®Google Scholar
• Box , G. E. P. and Meyer , R. D. , Dispersion Effects from Fractional Designs , Technometrics , 28 ( 1 ), 19 – 27 ( 1986 ).
   Web of Science ®Google Scholar
• Taguchi , G. , Elsayed , E. A. , Hsiang , T. C. , Quality Engineering in Production Systems , McGraw-Hill , New York , 1989 .
   Google Scholar
• Oh , H. L. , Variation Tolerant Design , in Proc. Conf. Uncertainty in Engineering Design ( 1988 ).
   Google Scholar
• Freund , J. E. and Simon , G. A. , Modern Elementary Statistics, , 9th ed. , Prentice-Hall , Englewood Cliffs , NJ , 1997 .
   Google Scholar
• Akao , Y. , Quality Function Deployment Integrating Customer Requirements into Product Design , Productivity Press , Cambridge , MA , 1990 .
   Google Scholar
• Cohen , L. , Quality Function Deployment How to Make QFD Work for You , Addison-Wesley , Reading , MA , 1994 .
   Google Scholar
• Saaty , T L. , The Analytic Hierarchy Process Planning, Priority Setting, Resource Allocation , McGraw-Hill , New York , 1980 .
   Google Scholar
• Montgomery , D. C. , Design and Analysis of Experiments, 3rd ed. , John Wiley & Sons , New York , 1991 .
   Google Scholar
• Hicks , C. R. , Fundamental Concepts in the Design of Experiments, 4th ed. , Saunders College , New York , 1993 .
   Google Scholar
• Box , G. E. P. and Draper , N. R. , Empirical Model-Building and Response Surfaces , John Wiley & Sons , New York , 1987 .
   Google Scholar
• Fogliatto , F. S. and Albin , S. L. , Variance of Predicted Response as an Optimization Criterion in Multiresponse Experiments , Qual. Eng ., 12 ( 4 ), 523 – 533 ( 2000 ),
   Google Scholar
• Microsoft , Excel, Ver. 5.0, User's Guide , Microsoft Co ., Redmond , WA , 1994 .
   Google Scholar
• Lindo Systems , What's Best, User's Manual , Lindo Systems Inc ., Chicago , 1998 .
   Google Scholar
• Lasdon , L. S. , Waren , A. D. , Jain , A. , and Ratner , M. , Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming , ACM Trans. Math. Software , 4 , 34 – 50 ( 1978 ).
   Google Scholar