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

Abstract

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.

A FT-NIR Process Analytical Technology Approach for Milk Renneting Control

“…Multivariate statistical process control (MSPC) charts have been used in the dairy industry for fault diagnosis in the monitoring of milk pasteurisation process [ 12 ]. However, limited research has been performed in the development of MSPC based on NIR signal for milk coagulation monitoring [ 13 ].…”