A LASSO-based batch process modeling and end-product quality prediction method

Abstract

A least absolute shrinkage and selection operator (LASSO) based batch process modeling and end-product quality prediction method is developed in this paper, which overcomes the shortcomings of both multiway partial least squares (MPLS) and the phase-based methods. The proposed phase-LASSO approach models not only the phase characteristics but also the within-phase and between-phase time-dependent information. In the meantime, it automatically selects the critical-to-quality phases via LASSO-type regularization. As a result, phase-LASSO has good prediction accuracy and model interpretation. The effectiveness of the proposed method is illustrated by the case study on injection molding.