HACCP with multivariate process monitoring and fault diagnosis techniques: application to a food pasteurization process

被引:14
|
作者
Tokatli, F
Cinar, A [1 ]
Schlesser, JE
机构
[1] IIT, Dept Chem & Environm Engn, Chicago, IL 60616 USA
[2] US FDA, Natl Ctr Food Safety & Technol, Summit Argo, IL 60501 USA
关键词
multivariate statistical process monitoring; fault diagnosis; HACCP;
D O I
10.1016/j.foodcont.2004.04.008
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Multivariate statistical process monitoring (SPM), and fault detection and diagnosis (FDD) methods are developed to monitor the critical control points (CCPs) in a continuous food pasteurization process. Multivariate SPM techniques effectively use information from all process variables to detect abnormal process behavior. Fault diagnosis techniques isolate the source cause of the deviation in process variable(s). The methods developed are illustrated by implementing them to monitor the critical control points and diagnose causes of abnormal operation of a high temperature short time (HTST) pasteurization pilot plant. The detection power of multivariate SPM and FDD techniques over univariate SPM techniques is shown and their integrated use to ensure the product safety and quality in food processes is demonstrated. (C) 2004 Published by Elsevier Ltd.
引用
收藏
页码:411 / 422
页数:12
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