Optimization of correlated multiple quality characteristics using desirability function

Quality Engineering

Volumn 17, Issue 1, 2005, Pages 119-126

  Wu, Ful Chiang ^a  

^a VAN NUNG INSTITUTE OF TECHNOLOGY   (Taiwan)

Author keywords

Correlation; Desirability function; Multiple quality characteristics; Robust design; Taguchi method

Indexed keywords

APPROXIMATION THEORY; CORRELATION METHODS; DESIGN; FUNCTION EVALUATION; MATHEMATICAL MODELS; MATHEMATICAL TRANSFORMATIONS; OPTIMIZATION; REGRESSION ANALYSIS;

DESIRABILITY FUNCTION; MULTIPLE QUALITY CHARACTERISTICS; ROBUST DESIGN; TAGUCHI METHOD;

QUALITY CONTROL;

EID: 24044525634     PISSN: 08982112     EISSN: None     Source Type: Journal    
DOI: 10.1081/QEN-200028725     Document Type: Article

References (23)

1. Carlyle, W. M., Montgomery, D. C., Runger, G. C. (2000). Optimization problems and methods in quality control and improvement. J. Qual. Technol. 32(1):1-16.
2. Chen, L.-H. (1997). Designing robust products with multiple quality characteristics. Comput. Oper. Res. 24(10):937-944.
3. Chiao, C.-H., Hamada, M. (2001). Analysis experiments with correlated multiple responses. J. Qual. Technol. 33(4):451-465.
4. Derringer, G., Suich, R. (1980). Simultaneous optimization of several response variables. J. Qual. Technol. 12(4):214-219.
5. Elsayed, E. A., Chen, A. (1993). Optimal levels of process parameters for products with multiple characteristics. Int. J. of Prod. Res. 31(5):1117-1132.
6. Jayaram, J. S. R., Ibrahim, Y. (1997). Robustness for multiple response problems using a loss model. Int. J. Qual. Sci. 2(3):199-205.
7. Khuri, A. I., Conlon, M. (1981). Simultaneous optimization of multiple responses represented by polynomial regression functions. Technometrics 23(4):363-375.
8. Lin, C. L., Lin, J. L., Ko, T. C. (2002). Optimisation of the EDM process based on the orthogonal array with fuzzy logic and grey relational analysis method. Int. J. Adv. Manuf. Technol. 19(4):271-277.
9. Logothetis, N., Haigh, A. (1988). Characterizing and optimizing multi-response processes by taguchi method. Qual. Reliab. Eng. Int. 4(2):159-169.
10. Lu, D., Antony, J. (2002). Optimization of multiple responses using a fuzzy-rule based inference system. Int. J. Prod. Res. 40(7):1613-1625.
11. Maghsoodloo, S., Chang, C.-L. (2001). Quadratic loss functions and signal-to-noise ratios for a bivariate response. J. Manuf. Syst. 20(1):1-12.
12. Phadke, M. S. (1989). Quality Engineering Using Robust Design. Englewood Cliffs, NJ: Prentice-Hall.
13. Pignatiello, J. J. (1993). Strategies for robust multi-response quality engineering. IIE Trans. 25(3):5-15.
14. Rao, C. R. (1973). Linear Statistical Inference and Its Application. New York, NY: John Wiley & Sons.
15. Reddy, P. B. S., Nishina, K., Babu, A. S. (1998). Taguchi's methodology for multi-response optimization - a case study in the Indian plastics industry. Int. J. Qual. Reliab. Manage. 15(6):646-668.
16. Su, C.-T., Tong, L.-I. (1997). Multi-response robust design by principal component analysis. T. Qual. Manage. 8(6):409-416.
17. Taguchi, G. (1990). Introduction to Quality Engineering. Tokyo, Japan: Asian Productivity Organization.
18. Tong, L.-I., Su, C.-T. (1997). Optimizing multi-response problems in the Taguchi method by fuzzy multiple attribute decision making. Qual. Reliab. Eng. Int. 13(1):25-34.
19. Tong, L.-I., Su, C.-T., Wang, C.-H. (1997). The optimization of multiresponse problems in the Taguchi method. Int. J. Qual. Reliab. Manage. 14(4):367-380.
20. Tsui, K.-L. (1999). Robust design optimization for multiple characteristics problems. Int. J. Prod. Res. 37(2):433-445.
21. Vining, G. G. (1998). A compromise approach to multiresponse optimization. J. Qual. Technol. 30(4):309-313.
22. Wu, C. F. J., Hamada, M. (2000). Experiments: Planning, Analysis, and Parameter Design Optimization. New York, NY: Wiley-Interscience.
23. Wu, F.-C. (2002). Optimisation of multiple quality characteristics based on percentage reduction of Taguchi's quality loss. Int. J. Adv. Manuf. Technol. 20(10):749-753.