How to cite this paper
Gauri, S. (2014). Optimization of multi-response dynamic systems using principal component analysis (PCA)-based utility theory approach.International Journal of Industrial Engineering Computations , 5(1), 101-114.
Refrences
Bae, S.J., & Tsui, K.L. (2006). Analysis of dynamic robust design experiment with explicit & hidden noise variables. Quality Technology & Quantitative Management, 3, 55-75.
Chang, H.H. (2006). Dynamic multi-response experiments by back propagation networks and desirability functions. Journal of the Chinese Institute of Industrial Engineers, 23, 280-288.
Chang, H.H. (2008). A data mining approach to dynamic multiple responses in Taguchi experimental design. Expert System with Applications, 35, 1095-1103.
Chang, H.H., & Chen, Y.K. (2011). Neuro-genetic approach to optimize parameter design of dynamic multiresponse experiments. Applied Soft Computing, 11, 436 – 442.
Chen, S.P. (2003). Robust design with dynamic characteristics using stochastic sequential quadratic programming. Engineering Optimization, 35, 79-89.
Derek, W.B. (1982). Analysis of Optimal Decisions. New York: John Wiley and Sons.
Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12, 214–219.
Hsieh, K.L., Tong, L.I., Chiu, H.P., & Yeh, H.Y. (2005). Optimization of a multi-response problem in Taguchi’s dynamic system. Computers and Industrial Engineering, 49, 556-571.
Jeong, I.N., & Kim, K.J. (2009). An interactive desirability function method to multiresponse optimization. European Journal of Operational Research, 195, 412–426.
Joseph, V.R., & Wu, C.F.J. (2002). Robust parameter design of multiple-target systems. Technometrics, 44, 338-346.
Khuri, A.I., & Conlon, M. (1981). Simultaneous optimization of multiple responses represented by polynomial regression functions. Technometrics, 23, 363–375.
Kim, K.J. & Lee, D.K.J. (2006). Optimization of multiple responses considering both location and dispersion effects. European Journal of Operational Research, 169, 133-145.
Kumar, P., Barua, P.B., & Gaindhar, J.L. (2000). Quality optimisation (multi-characteristics) through Taguchi technique and utility concept. Quality and Reliability Engineering International, Vol. 16, pp. 475-485.
Lesperance, M.L., & Park, S.M. (2003). GLMs for the analysis of robust designs with dynamic characteristics. Journal of Quality Technology, 35, 253-263.
Liao, H.C. (2006). Multi-response optimization using weighted principal component. International Journal on Advanced Manufacturing Technology, 27, 720-725.
Lunani, M., Nair, V.N., & Wasserman, G.S. (1997). Graphical methods for robust design with dynamic characteristics. Journal of Quality Technology, 29, 327-338.
McCaskey, S.D., & Tsui, K.L. (1997). Analysis of dynamic robust design experiments. International Journal of Production Research, 35, 1561-1574.
Miller, A., & Wu, C.F.J. (1996). Parameter design for signal-response systems: A different look at Taguchi & apos; s dynamic parameter design. Statistical Science, 11, 122-136.
Pal, S., & Gauri, S.K. (2010a). Multi-response optimization using multiple regression based weighted signal-to-noise ratio (MRWSN). Quality Engineering, 22, 336-350.
Pal, S., & Gauri, S.K. (2010b). Assessing effectiveness of the various performance metrics for multi-response optimization using multiple regression. Computers and Industrial Engineering, 59, 976-985.
Pignatiello, J.J. (1993). Strategies for robust multi-response quality engineering. Industrial Engineering Research Development-IIET, 25, 5–15.
Su, C.T., & Tong, L.I. (1997). Multi-response robust design by principal component analysis. Total Quality Management, 8, 409–416.
Su, C.T., Chen, H.L., & Chan, H.L. (2005). Applying neural network and scatter search to optimize parameter design with dynamic characteristics. Journal of the Operational Research Society, 56, 1132-1140.
Taguchi, G. (1990). Introduction to Quality Engineering. Tokyo, Japan: Asian Productivity Organization.
Tong, L.I., & Hsieh, K.L. (2001). A novel means of Applying artificial neural networks to optimize multi-response problem. Quality Engineering, 13, 11–18.
Tong, L.I., Wang, C.H., Houng, J.Y., & Chen, J.Y. (2002). Optimizing dynamic multiresponse problems using the dual-response-surface method. Quality Engineering, 14, 115-125.
Tong, L.I., Wang, C.H., Chen, C.C., & Chen, C.T. (2004). Dynamic multiple responses by ideal solution analysis. European Journal of Operational Research, 156, 433-441.
Tong, L.I., Chen, C.C., & Wang, C.H. (2007). Optimization of multi-response processes using the VIKOR method. International Journal on Advanced Manufacturing Technology, 31, 1049-1057.
Tong, L.I., Wang, C.H., & Tsai, C.W. (2008). Robust design for multiple dynamic quality characteristics using data envelopment analysis. Quality and Reliability Engineering International, 24, 557-571.
Tsui, K. (1999). Modelling and analysis of dynamic robust design experiments. IIE Transactions, 31, 1113 – 1122.
Wang, C.H. (2007). Dynamic multi-response optimization using principal component analysis and multiple criteria evaluation of the grey relation model. International Journal on Advanced Manufacturing Technology, 32, 617-624.
Wasserman, G.S. (1996). Parameter design with dynamic characteristics: A regression perspective. Quality and Reliability Engineering International, 12, 113-117.
Wu, C.F.J., & Hamada, M. (2000). Experiments: Planning, analysis, and parameter design optimization. New York: Wiley-Interscience.
Wu, C.F.J. (2005). Optimization of correlated multiple quality characteristics using desirability function. Quality Engineering, 17, 119-126.
Wu, C.F.J. (2009). Robust design of nonlinear multiple dynamic quality characteristics. Computers and Industrial Engineering, 56, 1328-1332.
Chang, H.H. (2006). Dynamic multi-response experiments by back propagation networks and desirability functions. Journal of the Chinese Institute of Industrial Engineers, 23, 280-288.
Chang, H.H. (2008). A data mining approach to dynamic multiple responses in Taguchi experimental design. Expert System with Applications, 35, 1095-1103.
Chang, H.H., & Chen, Y.K. (2011). Neuro-genetic approach to optimize parameter design of dynamic multiresponse experiments. Applied Soft Computing, 11, 436 – 442.
Chen, S.P. (2003). Robust design with dynamic characteristics using stochastic sequential quadratic programming. Engineering Optimization, 35, 79-89.
Derek, W.B. (1982). Analysis of Optimal Decisions. New York: John Wiley and Sons.
Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12, 214–219.
Hsieh, K.L., Tong, L.I., Chiu, H.P., & Yeh, H.Y. (2005). Optimization of a multi-response problem in Taguchi’s dynamic system. Computers and Industrial Engineering, 49, 556-571.
Jeong, I.N., & Kim, K.J. (2009). An interactive desirability function method to multiresponse optimization. European Journal of Operational Research, 195, 412–426.
Joseph, V.R., & Wu, C.F.J. (2002). Robust parameter design of multiple-target systems. Technometrics, 44, 338-346.
Khuri, A.I., & Conlon, M. (1981). Simultaneous optimization of multiple responses represented by polynomial regression functions. Technometrics, 23, 363–375.
Kim, K.J. & Lee, D.K.J. (2006). Optimization of multiple responses considering both location and dispersion effects. European Journal of Operational Research, 169, 133-145.
Kumar, P., Barua, P.B., & Gaindhar, J.L. (2000). Quality optimisation (multi-characteristics) through Taguchi technique and utility concept. Quality and Reliability Engineering International, Vol. 16, pp. 475-485.
Lesperance, M.L., & Park, S.M. (2003). GLMs for the analysis of robust designs with dynamic characteristics. Journal of Quality Technology, 35, 253-263.
Liao, H.C. (2006). Multi-response optimization using weighted principal component. International Journal on Advanced Manufacturing Technology, 27, 720-725.
Lunani, M., Nair, V.N., & Wasserman, G.S. (1997). Graphical methods for robust design with dynamic characteristics. Journal of Quality Technology, 29, 327-338.
McCaskey, S.D., & Tsui, K.L. (1997). Analysis of dynamic robust design experiments. International Journal of Production Research, 35, 1561-1574.
Miller, A., & Wu, C.F.J. (1996). Parameter design for signal-response systems: A different look at Taguchi & apos; s dynamic parameter design. Statistical Science, 11, 122-136.
Pal, S., & Gauri, S.K. (2010a). Multi-response optimization using multiple regression based weighted signal-to-noise ratio (MRWSN). Quality Engineering, 22, 336-350.
Pal, S., & Gauri, S.K. (2010b). Assessing effectiveness of the various performance metrics for multi-response optimization using multiple regression. Computers and Industrial Engineering, 59, 976-985.
Pignatiello, J.J. (1993). Strategies for robust multi-response quality engineering. Industrial Engineering Research Development-IIET, 25, 5–15.
Su, C.T., & Tong, L.I. (1997). Multi-response robust design by principal component analysis. Total Quality Management, 8, 409–416.
Su, C.T., Chen, H.L., & Chan, H.L. (2005). Applying neural network and scatter search to optimize parameter design with dynamic characteristics. Journal of the Operational Research Society, 56, 1132-1140.
Taguchi, G. (1990). Introduction to Quality Engineering. Tokyo, Japan: Asian Productivity Organization.
Tong, L.I., & Hsieh, K.L. (2001). A novel means of Applying artificial neural networks to optimize multi-response problem. Quality Engineering, 13, 11–18.
Tong, L.I., Wang, C.H., Houng, J.Y., & Chen, J.Y. (2002). Optimizing dynamic multiresponse problems using the dual-response-surface method. Quality Engineering, 14, 115-125.
Tong, L.I., Wang, C.H., Chen, C.C., & Chen, C.T. (2004). Dynamic multiple responses by ideal solution analysis. European Journal of Operational Research, 156, 433-441.
Tong, L.I., Chen, C.C., & Wang, C.H. (2007). Optimization of multi-response processes using the VIKOR method. International Journal on Advanced Manufacturing Technology, 31, 1049-1057.
Tong, L.I., Wang, C.H., & Tsai, C.W. (2008). Robust design for multiple dynamic quality characteristics using data envelopment analysis. Quality and Reliability Engineering International, 24, 557-571.
Tsui, K. (1999). Modelling and analysis of dynamic robust design experiments. IIE Transactions, 31, 1113 – 1122.
Wang, C.H. (2007). Dynamic multi-response optimization using principal component analysis and multiple criteria evaluation of the grey relation model. International Journal on Advanced Manufacturing Technology, 32, 617-624.
Wasserman, G.S. (1996). Parameter design with dynamic characteristics: A regression perspective. Quality and Reliability Engineering International, 12, 113-117.
Wu, C.F.J., & Hamada, M. (2000). Experiments: Planning, analysis, and parameter design optimization. New York: Wiley-Interscience.
Wu, C.F.J. (2005). Optimization of correlated multiple quality characteristics using desirability function. Quality Engineering, 17, 119-126.
Wu, C.F.J. (2009). Robust design of nonlinear multiple dynamic quality characteristics. Computers and Industrial Engineering, 56, 1328-1332.