First-Principles Model Diagnosis in Batch Systems by Multivariate Statistical Modeling

Abstract Process/model mismatch may arise when a first-principles model is challenged against historical experimental data. In this study, a methodology recently proposed to diagnose the root cause of the mismatch in continuous processes is extended to batch systems, taking a batch drying process as a case study to test the proposed methodology. The likely sources of the mismatch are identified using a multivariate statistical model and analyzing the model residuals as well as the scores shifts. Two simulated examples demonstrate the effectiveness of the proposed methodology.