Industrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosis
ProcessesPublished 30 June 2017Open access
Marco S. Reis, Geert Gins
Citations283
SJR quartileQ2
SJR score0.55
SNIP0.86
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TL;DR
A critical outlook of the evolution of Industrial Process Monitoring since its introduction almost 100 years ago is provided, including the strong interplay of the Process and Maintenance departments, hitherto managed as separated silos.
Abstract
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.
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Decision SciencesEngineering
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