Cooperative Process Optimization between Paper Machines and Stock Preparation Utilizing Plant Big Data Analysis, 18PaperCon

Real-time process data from distributed control systems (DCSs) have not been extensively used for optimizing production processes, except for the data that are directly used for real-time control and monitoring in plant operations. In this paper, we introduce the development and application of a cooperative process optimization system whereby real-time process data are collected for an extended period of time from DCSs installed in multiple processes. By applying statistical techniques and the latest process control theory (FRIT controller tuning method), we have improved the fluctuations and interference between paper machines and stock preparation processes. This attenuation of the fluctuations has brought about a drastic reduction of transition time in grade changes, and has eventually en hanced production efficiency and quality. This result has never been achieved by conventional approaches. 

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