IMPROVED PROCESS UNDERSTANDING USING MULTIWAY PRINCIPAL COMPONENT ANALYSIS

Producing a uniform polymer by batch processing is important for the f ollowing reasons: to improve the downstream processing performance, to enable material produced at one site to be used by another, and to re main competitive. Eliminating the sources of batch-to-batch variabilit y and tightening the control of key variables are but two ways to acco mplish these objectives. In this work, it is shown that multiway princ ipal component analysis (MPCA) can be used to identify major sources o f variability in the processing steps. The results show that the major source of batch-to-batch variability is due to reactor temperature va riations arising from disturbances in the heating system and other hea t-transfer limitations. Correlations between the variations in the pro cessing steps and the final product properties are found, and recommen dations to reduce the sources of variations are discussed.