Inferential quality assessment in breakfast cereal production

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. (C) 2001 Elsevier Science Ltd. All rights reserved.