Abstract
In this paper, a two-dimensional, two-layer quality regression model is established to monitor multi-phase, multi-mode batch processes. Firstly, aiming at the multi-phase problem and the multi-mode problem simultaneously, the relations among modes and phases are captured through the analysis between process variables and quality variables by establishing a two-dimensional, two-layer regression partial least squares (PLS) model. The two-dimensional regression traces the intra-batch and inter-batch characteristics, while the two-layer structure establishes the relationship between the target process and historical modes and phases. Consequently, online monitoring is carried out for multi-phase, multi-mode batch processes based on quality prediction. In addition, the online quality prediction and monitoring results based on the proposed method and those based on the traditional phase mean PLS method are compared to prove the effectiveness of the proposed method.
Highlights
Batch process is a way of production closely related to people’s life in the modern process industry
Multi-phase characteristic and multi-mode characteristic exist in batch processes simultaneously, which makes the batch processes complex and interesting for researchers
Process data of batch processes are stored in data matrix X(I × Jx × K), where I refers to the number of batches; Jx refers to the number of process variables; and K
Summary
Batch process is a way of production closely related to people’s life in the modern process industry. Two-Dimensional, Two-Layer Quality Regression Model Based Batch Process Monitoring.
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