Abstract
In batch processing, not only the characteristics of different phases are different, but also there may be different characteristics between batches. These characteristics of different phases and batches will have different effects on the final product quality. In order to enhance the safety of batch processes, it is necessary to establish an appropriate monitoring system to monitor the production process based on quality-related information. In this work, based on multi-phase and multi-mode quality prediction, a new quality-analysis-based process-monitoring strategy is developed for batch processes. Firstly, the time-slice models are established to determine the critical-to-quality phases. Secondly, a multi-phase residual recursive model is established using each quality residual of the phase mean models. Subsequently, a new process-monitoring strategy based on quality analysis is proposed for a single mode. After that, multi-mode quality analysis is carried out to judge the relevance between the historical modes and the new mode. Further, online quality prediction is achieved applying the selected model based on multi-mode quality analysis, and an according process-monitoring strategy is developed. The simulation results show the availability of this method for multi-phase multi-mode batch processes.
Highlights
Both multi-phase quality analysis and multi-mode quality analysis are conducted at the same time to develop a comprehensive process-monitoring strategy based on the quality prediction of batch processes
Because of the above characteristics of batch processes, a phase that has a significant contribution to the final quality is defined as the critical-to-quality phase
The index R2, which is used to describe the goodness of fit of the regression model in the field of multivariable linear regression, is used to measure the influence of each time slice on the final quality. Those time slices with high R2 are identified to be critical to quality, and the phases with these time slices are identified as critical-toquality phases
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Due to the calibration and modeling problems caused by operation switching (or moving to different phases), a new evolutionary PLS method is proposed, which can be used to predict intermediate quality measurement and to detect process faults avoiding false positives [24]. In this work, both multi-phase quality analysis and multi-mode quality analysis are conducted at the same time to develop a comprehensive process-monitoring strategy based on the quality prediction of batch processes.
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