Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/108332
DC FieldValueLanguage
dc.contributor.authorReis, Marco S.-
dc.contributor.authorGins, Geert-
dc.date.accessioned2023-08-24T10:39:51Z-
dc.date.available2023-08-24T10:39:51Z-
dc.date.issued2017-
dc.identifier.issn2227-9717pt
dc.identifier.urihttps://hdl.handle.net/10316/108332-
dc.description.abstractWe 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.pt
dc.language.isoengpt
dc.publisherMDPIpt
dc.relationproject 016658 (references PTDC/QEQ-EPS/1323/2014, POCI-01-0145-FEDER-016658) financed by Project 3599-PPCDT (Promover a Produção Científica e Desenvolvimento Tecnológico e a Constituição de Redes Temáticas) and co-financed by the European Union’s FEDERpt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectindustrial process monitoringpt
dc.subjectfault detection and diagnosispt
dc.subjectprognosispt
dc.subjectprocess healthpt
dc.subjectequipment healthpt
dc.titleIndustrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosispt
dc.typearticle-
degois.publication.firstPage35pt
degois.publication.issue3pt
degois.publication.titleProcessespt
dc.peerreviewedyespt
dc.identifier.doi10.3390/pr5030035pt
degois.publication.volume5pt
dc.date.embargo2017-01-01*
uc.date.periodoEmbargo0pt
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.fulltextCom Texto completo-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.author.researchunitCIEPQPF – Chemical Process Engineering and Forest Products Research Centre-
crisitem.author.parentresearchunitFaculty of Sciences and Technology-
crisitem.author.orcid0000-0002-4997-8865-
Appears in Collections:I&D CERES - Artigos em Revistas Internacionais
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This item is licensed under a Creative Commons License Creative Commons