Just-In-Time Statistical Process Control: Adaptive Monitoring of Vinyl Acetate Monomer Process

摘要

A new fault detection method is proposed to realize adaptive high-performance monitoring and efficient maintenance of the system. The proposed method is data-driven and called Just-In-Time Statistical Process Control (JIT-SPC). JIT-SPC focuses on the distance from the current operation data to the normal operation data stored in the database, because fault detection depends essentially on whether normal data exist near the current data or not. Since JIT-SPC is a model-free technique without impractical assumptions that conventional methods make, it has a potential for realizing practical, adaptive, high-performance monitoring. In addition, fault identification can be done through contribution plot in the framework of JIT-SPC. The usefulness of JIT-SPC and its contribution plot is demonstrated through a case study of the vinyl acetate monomer process. The results show that JIT-SPC can cope with changes in operating condition and can detect faults earlier than the conventional MSPC.