Detection and diagnosis of abnormal batch operations based on multi-way principal component analysis
- Authors
- Paul Nomikos
- Published
- 1996
- DOI
- 10.1016/S0019-0578(96)00035-3
- Citation
- Nomikos: "Detection and diagnosis of abnormal batch operations based on multi-way principal component analysis", ISA Transactions, 35, 259-266, 1996.
- Abstract
- The industrial application of a new monitoring scheme for batch and semi-batch processes is presented. Multi-way Principal Component Analysis is used to analyze the information from the on-line process measurements. The basic idea is to build a statistical model based on process measurements from past successful batches, which describes the normal operation of the process. Subsequently future batches are compared against this model and characterized as normal or abnormal. The algorithms and all the design equations are presented for setting up Statistical Process Control charts which monitor the performance of a batch process. Contribution plots for detected abnormal operations are developed to identify the measurement variables and time periods of abnormal operation.
- Tags
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