An industrial perspective on implementing on-line applications of multivariate statistics

被引:70
作者
Miletic, I
Quinn, S
Dudzic, M
Vaculik, V
Champagne, M
机构
[1] Dofasco Ltd, Hamilton, ON L8N 3J5, Canada
[2] Tembec Inc, Temiscaming, PQ J0Z 3R0, Canada
关键词
principal component analysis; partial least squares; correlation; regression; fault detection; process operation; steel manufacturing; pulp and paper production;
D O I
10.1016/j.jprocont.2004.02.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Multivariate statistics (MVS) has enjoyed popularity in the applied science literature over the last decade. It has also been well received by industrial practitioners; however, industrial applications have had mixed results. In this paper, we focus on our experiences in developing multivariate statistical systems for industrial use. From these experiences, we identify a methodology for developing useful, long-standing industrial applications. We highlight features we feel are important in the successful development of on-line MVS applications, both technical and non-technical. Specifically, we focus on on-line systems for manufacturing environments. Many of the applications discussed grew out of industry-university collaborations. To end the paper, we recommend topics open for further academic research with an industrial focus. (C) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:821 / 836
页数:16
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