LAPSE:2018.0241
Published Article
LAPSE:2018.0241
Industrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosis
Marco S. Reis, Geert Gins
July 31, 2018
We provide a critical outlook of the evolution of Industrial Process Monitoring (IPM) since its introduction almost 100 years ago. Several evolution trends that have been structuring IPM developments over this extended period of time are briefly referred, with more focus on data-driven approaches. We also argue that, besides such trends, the research focus has also evolved. The initial period was centred on optimizing IPM detection performance. More recently, root cause analysis and diagnosis gained importance and a variety of approaches were proposed to expand IPM with this new and important monitoring dimension. We believe that, in the future, the emphasis will be to bring yet another dimension to IPM: prognosis. Some perspectives are put forward in this regard, including the strong interplay of the Process and Maintenance departments, hitherto managed as separated silos.
Keywords
equipment health, fault detection and diagnosis, industrial process monitoring, process health, prognosis
Suggested Citation
Reis MS, Gins G. Industrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosis. (2018). LAPSE:2018.0241
Author Affiliations
Reis MS: CIEPQPF-Department of Chemical Engineering, University of Coimbra Polo II, Rua Sílvio Lima 3030-790, Coimbra, Portugal
Gins G: AIXIAL Belgium, Charleroise Steenweg 112, B-1060 Brussels, Belgium
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Journal Name
Processes
Volume
5
Issue
3
Article Number
E35
Year
2017
Publication Date
2017-06-30
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr5030035, Publication Type: Journal Article
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LAPSE:2018.0241
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doi:10.3390/pr5030035
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Jul 31, 2018
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