An Integrated Approach Based on Principal Component and Multivariate Process Capability for Simultaneous Optimization of Location and Dispersion for Correlated Multiple Response Problems

被引:10
作者
Bera, Sasadhar [1 ]
Mukherjee, Indrajit [2 ]
机构
[1] Indian Inst Management, Ranchi, Jharkhand, India
[2] Indian Inst Technol, Shailesh J Mehta Sch Management, Bombay, Maharashtra, India
关键词
dispersion effects; multiple response optimization; multivariate process capability index; principal component analysis; product quality; MULTIRESPONSE OPTIMIZATION; DESIRABILITY FUNCTIONS; SURFACE OPTIMIZATION; ROBUST DESIGN; NORMALITY; TAGUCHI; SYSTEMS;
D O I
10.1080/08982112.2013.765014
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Product quality is generally defined by a family of critical characteristics, or so-called responses. In this article, a new integrated approach is proposed that has the ability to reduce the response space dimensionality and also considers both location and dispersion effects in a correlated multiple response optimization problem. The proposed approach uses a principal component (PC)-based multivariate process capability index (MCpmk;PC) as an objective function for optimization. In addition, the nonlinear search algorithm can efficiently determine the best trade-off solution in the orthogonal PC space. Three different cases are selected to illustrate the effectiveness of the new proposed approach compared to a few selected existing approaches.
引用
收藏
页码:266 / 281
页数:16
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