Detecting multiple special causes from multivariate data with applications to fault detection in manufacturing

被引:12
作者
Zantek, Paul [1 ]
Li, Shan
Chen, Yong
机构
[1] Univ Maryland, Robert H Smith Sch Business, College Pk, MD 20742 USA
[2] Univ Iowa, Dept Mech & Ind Engn, Iowa City, IA 52242 USA
关键词
multivariate exponentially weighted moving average; multivariate process control; state-space models;
D O I
10.1080/07408170601089513
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Several articles in the recent literature propose linear models of product quality for both single station and multistation manufacturing processes. We show how these models may be used in conjunction with statistical methods to design a procedure for multivariate Statistical Process Control (SPC) that outperforms direct application of multivariate SPC. We show how to design the procedure and evaluate its performance in shift detection for models with and without singularities. The use of the procedure is illustrated using two examples from automobile body assembly.
引用
收藏
页码:771 / 782
页数:12
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