Case Study for Performance Assessment and Benefit Estimation in Paper Machines by Data Mining

Abstract In this work, the performance assessment study is done on a paper mill using an in-house analytics tool capable of data mining. The tool proposes a generic methodology for performance analysis and then shows its application on an industrial multi-grade paper making process. The tool framework facilitates data preprocessing and data mining, configuration and calculation of key performance indices (KPIs), benchmarking and gap analysis for benefit estimation. It also helps in better performance visualization and identification of the root cause of variations in performance in paper mills. To illustrate the concept, key results from performance analysis study done on a paper machine are presented and suggested measures to improve performance are discussed.