Improved Multiscale Multivariate Process Monitoring Methods

Sheriff, M. Ziyan; Karim, M. Nazmul; Kravaris, Costas; Nounou, Hazem; Nounou, Mohamed

doi:10.23919/acc50511.2021.9483359

Cited by 2 publications

References 15 publications

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Review of Multiscale Methods for Process Monitoring, With an Emphasis on Applications in Chemical Process Systems

et al. 2022

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Process monitoring has played an increasingly significant role in ensuring safe and efficient manufacturing operations in process industries over the past several years. Chemical process data is highly correlated and has multiscale characteristics in general. To overcome this concern, extensive work has been made for multiscale process monitoring for process plants during the past two decades. The recent success of multiscale methods in monitoring and controlling manufacturing processes has sparked interest in investigating these methods for process monitoring. This article aims to present a concise and critical overview of the applications of multiscale process monitoring methods in chemical processes. First objective is to identify the importance of multiscale methods for process monitoring. The second and main objective is the statistical and critical analysis for methods implementation, application area, types of data used, and various issues mentioned by previous researchers. In addition, the most important critical issues have been identified, and the capabilities and limitations of each method are discussed and highlighted. The reported literature focused mainly on fault detection and did not investigate the root-cause diagnosis of the detected faults. Further, the challenges and prospects in multiscale process monitoring in the chemical process industry have been featured for advancement.

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