Phase Transition Analysis Based Quality Prediction for Multi-phase Batch Processes

• Published in: Chinese journal of chemical engineering Vol. 20; no. 6; pp. 1191 - 1197
• Main Author: 赵露平 赵春晖 高福荣
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2012
• Subjects: Algorithms; batch process; Chemical engineering; Injection molding; Least squares method; Monitoring; multi-phase; On-line systems; partial least squares; Phase transformations; quality prediction; Regression; transition; 产品质量; 分析基; 注塑成型工艺; 相位信息; 相变; 质量预测; 间歇过程; quality prediction; multi-phase; partial least squares; batch process; transition
• ISSN: 1004-9541; 2210-321X
• DOI: 10.1016/S1004-9541(12)60607-7

Batch processes are usually involved with multiple phases in the time domain and many researches on process monitoring as well as quality prediction have been done using phase information. However, few of them consider phase transitions, though they exit widely in batch processes and have non-ignorable impacts on product qualities. In the present work, a phase-based partial least squares （PLS） method utilizing transition information is proposed to give both online and offline quality predictions. First, batch processes are divided into several phases using regression parameters other than prior process knowledge. Then both steady phases and transitions which have great influences on qualities are identified as critical-to-quality phases using statistical methods. Finally, based on the analysis of different characteristics of transitions and steady phases, an integrated algorithm is developed for quality prediction. The application to an injection molding process shows the effectiveness of the proposed algorithm in comparison with the traditional MPLS method and the phase-based PLS method.