Article2002

A Unified Approach for Dual Response Surface Optimization

107 citations0/0 files storedJournal of Quality Technology

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Optimal Experimental Design Methods Probabilistic and Robust Engineering Design Advanced Multi-Objective Optimization Algorithms

Abstract

The optimization of dual response systems in order to achieve better quality has been an important problem in the robust design of industrial products and processes. In this paper, we propose a goal programming approach to optimize a dual response system. The formulation is general enough to include some of the existing methods as special cases. For purposes of illustration and comparison, the proposed approach is applied to two examples. We show that by tuning the weights assigned to the respective targets for the mean and standard deviation, past results can easily be replicated using Excel Solver, the use of which further enhances the practical appeal of our formulation.

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References

1988Empirical Model Building and Response Surfaces 1980Simultaneous Optimization of Several Response Variables 1996Response Surface Methodology 1990Combining Taguchi and Response Surface Philosophies: A Dual Response Approach 1995Dual Response Surface Optimization 1981Simultaneous Optimization of Multiple Responses Represented by Polynomial Regression Functions 1993STRATEGIES FOR ROBUST MULTIRESPONSE QUALITY ENGINEERING 1993A Nonlinear Programming Solution to the Dual Response Problem

Cited by

2007Fortification of Six Sigma: expanding the DMAIC toolset 2012Ensemble of Surrogates for Dual Response Surface Modeling in Robust Parameter Design 2008Another view of dual response surface modeling and optimization in robust parameter design 2008Log-Normal Versus Gamma Models for Analyzing Data from Quality-Improvement Experiments 2012An Overview of Optimization Formulations for Multiresponse Surface Problems 2005Mean square error criteria to multiresponse process optimization by a new genetic algorithm

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