Taguchi Design optimization using multivariate process capability index

The Taguchi method is a useful technique to improve the performance of products or processes at a lower cost and in less time. This procedure can be categorized in the static and dynamic quality characteristics. The optimization of multiple responses has received increasing attention over the last few years in many manufacturing organizations.  Several approaches dealing with multiple static quality characteristic problems have been reported in the literature. However, little attention has been made on optimizing the multiple dynamic quality characteristics. In this paper, we investigate multivariate signal response systems (Dynamic Taguchi) and propose a method based on multivariate process capability. Simulated data shows that the proposed method can increase robustness of dynamic Taguchi method. Furthermore, proposed method is capable to find the optimal value of controllable factors in a continuous space.

[1]  Mahdi Bashiri,et al.  Non-normal multi-response optimization by multivariate process capability index , 2012 .

[2]  Paul L. Goethals,et al.  Robust parameter design in resource-constrained environments: An investigation of trade-offs between costs and precision within variable processes , 2013 .

[3]  Arden Miller,et al.  Parameter Design for Signal-Response Systems: A Different Look at Taguchi's Dynamic Parameter Design , 1996 .

[4]  Kwok-Leung Tsui.  Robust design optimization for multiple characteristic problems , 1999 .

[5]  Om Prakash Yadav,et al.  Reliability‐based robust design optimization: A multi‐objective framework using hybrid quality loss function , 2010, Qual. Reliab. Eng. Int..

[6]  Jerome Sacks,et al.  Computer Experiments for Quality Control by Parameter Design , 1990 .

[7]  C. L. Lin,et al.  Optimisation of the EDM Process Based on the Orthogonal Array with Fuzzy Logic and Grey Relational Analysis Method , .

[8]  Ravindra Khattree,et al.  ROBUST PARAMETER DESIGN : A RESPONSE SURFACE APPROACH , 1996 .

[9]  Chao-Ton Su,et al.  The optimization of multi‐response problems in the Taguchi method , 1997 .

[10]  Karen A. F. Copeland.  Experiments: Planning, Analysis, and Parameter Design Optimization , 2002 .

[11]  Arden Miller,et al.  Robust Design of Measurement Systems , 2010, Technometrics.

[12]  Gregory L. Boylan,et al.  Solving the Multidisciplinary Robust Parameter Design Problem for Mixed Type Quality Characteristics under Asymmetric Conditions , 2014, Qual. Reliab. Eng. Int..

[13]  Ida Gremyr,et al.  Principles of robust design methodology , 2008, Qual. Reliab. Eng. Int..

[14]  G. Geoffrey Vining,et al.  A Compromise Approach to Multiresponse Optimization , 1998 .

[15]  Arden Miller,et al.  Analysis of Parameter Design Experiments for Signal-Response Systems , 2002 .

[16]  Arden Miller,et al.  Commentary on taguchi's parameter design with dynamic characteristics , 1996 .

[17]  Kwok-Leung Tsui,et al.  Economical experimentation methods for robust design , 1991 .

[18]  Sung-Min Park,et al.  GLMs for the Analysis of Robust Designs with Dynamic Characteristics , 2003 .

[19]  M. Bashiri,et al.  A DATA ENVELOPMENT ANALYSIS METHOD FOR OPTIMIZING MULTI-RESPONSE PROBLEM BY DYNAMIC TAGUCHI METHOD , 2012 .

[20]  Murat Kulahci,et al.  Analysis of signal–response systems using generalized linear mixed models , 2010, Qual. Reliab. Eng. Int..

[21]  S. C. Sekhar,et al.  Optimization of cooling coil performance during operation stages for improved humidity control , 2009 .

[22]  Mahdi Bashiri,et al.  A New Multivariate Process Capability Index Under Both Unilateral and Bilateral Quality Characteristics , 2012, Qual. Reliab. Eng. Int..

[23]  Gary S. Wasserman,et al.  Graphical methods for robust design with dynamic characteristics , 1997 .

[24]  Chi-Hao Yeh,et al.  Robust design of multiple dynamic quality characteristics , 2005 .

[25]  Jamison V. Kovach,et al.  Multiresponse optimization using multivariate process capability index , 2011, Qual. Reliab. Eng. Int..

[26]  V. R. Joseph,et al.  Performance Measures in Dynamic Parameter Design , 2002 .

[27]  Zong Zhi-yu,et al.  A new desirability function based method for multi-response robust parameter design , 2006 .

[28]  Zhen He,et al.  A robust desirability function method for multi-response surface optimization considering model uncertainty , 2012, Eur. J. Oper. Res..

[29]  Hsu-Hwa Chang,et al.  A data mining approach to dynamic multiple responses in Taguchi experimental design , 2008, Expert Syst. Appl..

[30]  Ful-Chiang Wu.  Optimisation of Multiple Quality Characteristics Based on Percentage Reduction of Taguchi’s Quality Loss , 2002 .

[31]  Gary S. Wasserman.  Parameter design with dynamic characteristics : A regression perspective , 1996 .

[32]  Surajit Pal,et al.  Multi-Response Optimization Using Multiple Regression–Based Weighted Signal-to-Noise Ratio (MRWSN) , 2010 .

[33]  Kwok-Leung Tsui,et al.  Analysis of dynamic robust design experiments , 1997 .

[34]  Jiju Antony,et al.  Optimization of multiple responses using a fuzzy-rule based inference system , 2002 .

[35]  A. Khuri,et al.  Simultaneous Optimization of Multiple Responses Represented by Polynomial Regression Functions , 1981 .

[36]  K. Tsui.  Modeling and analysis of dynamic robust design experiments , 1999 .

[37]  C. Su,et al.  Multi-response robust design by principal component analysis , 1997 .

[38]  Chao-Ton Su,et al.  Applying neural network approach to achieve robust design for dynamic quality characteristics , 1998 .

[39]  Sangmun Shin,et al.  Robust design modelling and optimisation using response surface methodology and inverse problem , 2011 .

[40]  V. Roshan Joseph,et al.  Robust Parameter Design of Multiple-Target Systems , 2002, Technometrics.

[41]  Lee-Ing Tong,et al.  Optimizing Dynamic Multiresponse Problems Using the Dual-Response-Surface Method , 2002 .