Process monitoring and fault detection on a hot-melt extrusion process using in-line Raman spectroscopy and a hybrid soft sensor
Tahir, Furqan and Islam, Muhammad T. and Mack, John and Robertson, John and Lovett, David (2019) Process monitoring and fault detection on a hot-melt extrusion process using in-line Raman spectroscopy and a hybrid soft sensor. Computers and Chemical Engineering, 125. pp. 400-414. ISSN 0098-1354 (https://doi.org/10.1016/j.compchemeng.2019.03.019)
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Abstract
We propose a real-time process monitoring and fault detection scheme for a pharmaceutical hot-melt extrusion process producing Paracetamol-Affinisol extrudate. The scheme involves prediction of Paracetamol concentration from two independent sources: a hybrid soft sensor and a Raman-based Partial Least Squares (PLS) calibration model. Both these predictions are used by the developed PCA (Principal Component Analysis) and SPC (Statistical Process Control) monitors to detect process faults and raise alarms. Through real-time extrusion results, it is shown that this two-sensor approach enables the detection of various common process faults which would otherwise remain undetected with a single-sensor monitoring scheme.
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Item type: Article ID code: 67517 Dates: DateEvent9 June 2019Published25 March 2019Published Online13 March 2019Accepted14 May 2018SubmittedSubjects: Medicine > Therapeutics. Pharmacology
Technology > Engineering (General). Civil engineering (General) > BioengineeringDepartment: Faculty of Science > Strathclyde Institute of Pharmacy and Biomedical Sciences Depositing user: Pure Administrator Date deposited: 08 Apr 2019 13:50 Last modified: 06 Jul 2024 00:52 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/67517