Industrial implementation of an inline near infrared process control system for the production of caramel Article Swipe
YOU?
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· 2023
· Open Access
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· DOI: https://doi.org/10.1016/j.jfoodeng.2023.111717
· OA: W4386258039
This paper describes the implementation of inline near infrared spectroscopy measurements to determine the key quality attributes of caramel in an industrial manufacturing process. The current control strategy is based around offline sampling and laboratory analysis which is costly, time-consuming and compromises operational control. Moving to inline analysis overcomes these limitations but the development of robust calibration models is a challenging task. Product recipe changes and natural raw material variation compound the issues arising in typical calibration model development. It is demonstrated that with appropriate spectroscopic signal pre-treatment and pattern recognition algorithm analysis, it is possible to provide the operators with a robust assessment of the caramel key quality measures so that they can respond in a timely manner if further processing actions are required. Results demonstrate the ability for NIR measurement to detect batch deviations that subsequently were judged to fall outside of the quality control limits as determined in pre-release laboratory assessment.
