Improved process understanding using multiway principal component analysis

Producing a uniform polymer by batch processing is important for the following reasons: to improve the downstream processing performance, to enable material produced at one site to be used by another, and to remain competitive. Eliminating the sources of batch-to-batch variability and tightening the control of key variables are but two ways to accomplish these objectives. In this work, it is shown that multiway principal component analysis (MPCA) can be used to identify major sources of variability in the processing steps. The results show that the major source of batch-to-batch variability is due to reactor temperature variations arising from disturbances in the heating system and other heat-transfer limitations. Correlations between the variations in the processing steps and the final product properties are found, and recommendations to reduce the sources of variations are discussed.