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Inferential quality assessment in breakfast cereal production

Lookup NU author(s): Dr Hugo Hiden, Professor Elaine Martin, Professor Gary Montague, Emeritus Professor Julian Morris


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This paper describes the development of inferential models for the provision of real-time, on-line estimates of the quality of a breakfast cereal for production line operators. Five quality variables were selected and on-line measurements reflective of the key process conditions were identified. Following process data logging, a number of linear and non-linear data-based modelling methods were applied to identify relationships between the on-line measurements and the product quality. Off-line verification of the models indicated that the prediction accuracy achieved was sufficient to offer the opportunity for quality control improvements. The models were subsequently implemented on-line to provide the process operators with frequent estimates of product quality. Performance assessment has indicated a reduction in the variability of all five quality parameters. In addition to details of the modelling, the decisions relating to the development strategy and justification for implementation are considered. © 2001 Elsevier Science Ltd. All rights reserved.

Publication metadata

Author(s): Martin EB; Hiden H; Montague GA; Morris AJ; Albert S; Conlin A

Publication type: Article

Publication status: Published

Journal: Journal of Food Engineering

Year: 2001

Volume: 50

Issue: 3

Pages: 157-166

Print publication date: 01/11/2001

ISSN (print): 0260-8774

ISSN (electronic): 1873-5770

Publisher: Elsevier

URL: .htp://

DOI: 10.1016/S0260-8774(00)00238-7


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