Abstract

A process analysis and quality prediction scheme is proposed based on a stage-based PLS modeling for batch processes. Without any requirement of prior process knowledge, the scheme first divides a batch process into stages of different process characteristics. Subsequently, a strategy is developed to identify stages that have critical influences on concerned qualities, defined as critical-to-quality stages. Within these critical-to-quality stages, an algorithm is then further developed to identify the variables that have significant contributions to the quality variations. Finally, based on the identified nature of quality and stage relationships, a set of algorithms is developed for online quality prediction. The applications of the proposed scheme to injection molding show that the proposed analysis and quality prediction are not only effective but are also able to enhance process understanding and identify specific variables and periods for quality improvement.

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