Publication
Systematic review of predictive maintenance practices in the manufacturing sector
| datacite.subject.fos | Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | |
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| dc.contributor.author | Benhanifia, Abdeldjalil | |
| dc.contributor.author | Cheikh, Zied Ben | |
| dc.contributor.author | Oliveira, Paulo Moura | |
| dc.contributor.author | Valente, Antonio | |
| dc.contributor.author | Lima, José | |
| dc.date.accessioned | 2025-07-11T09:29:31Z | |
| dc.date.available | 2025-07-11T09:29:31Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Predictive maintenance (PDM) is emerging as a strong transformative tool within Industry 4.0, enabling significant improvements in the sustainability and efficiency of manufacturing processes. This in-depth literature review, which follows the PRISMA 2020 framework, examines how PDM is being implemented in several areas of the manufacturing industry, focusing on how it is taking advantage of technological advances such as artificial intelligence (AI) and the Internet of Things (IoT). The presented in-depth evaluation of the technological principles, implementation methods, economic consequences, and operational improvements based on academic and industrial sources and new innovations is performed. According to the studies, integrating CDM can significantly increase machine uptime and reliability while reducing maintenance costs. In addition, the transition to PDM systems that use real-time data to predict faults and plan maintenance more accurately holds out promising prospects. However, there are still gaps in the overall methodologies for measuring the return on investment of PDM implementations, suggesting an essential research direction. | eng |
| dc.description.sponsorship | The authors are grateful to the Foundation for Science and Tech- nology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757 /2020) and SusTEC (LA/P/0007/2021). During the preparation of this work the author(s) used [Gramarly/ Quilbolt/chagpt] in order to [improve the language and correct the sentences and get an adequat analysis and relie information]. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication. | |
| dc.identifier.citation | Benhanifia, Abdeldjalil; Ben Cheikh, Zied; Oliveira, Paulo Moura; Valente, Antonio; Lima, José (2025). Systematic review of predictive maintenance practices in the manufacturing sector. Intelligent Systems with Applications. ISSN 2667-3053. 26, p. 1-17 | |
| dc.identifier.doi | 10.1016/j.iswa.2025.200501 | |
| dc.identifier.issn | 2667-3053 | |
| dc.identifier.uri | http://hdl.handle.net/10198/34664 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Elsevier | |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.relation | Research Centre in Digitalization and Intelligent Robotics | |
| dc.relation.ispartof | Intelligent Systems with Applications | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Predictive maintenance | |
| dc.subject | Fault diagnosis systems | |
| dc.subject | Artificial intelligence in manufacturing | |
| dc.subject | Real-time monitoring | |
| dc.title | Systematic review of predictive maintenance practices in the manufacturing sector | eng |
| dc.type | working paper | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardTitle | Research Centre in Digitalization and Intelligent Robotics | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT | |
| oaire.citation.endPage | 17 | |
| oaire.citation.startPage | 1 | |
| oaire.citation.title | Intelligent Systems with Applications | |
| oaire.citation.volume | 26 | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Lima | |
| person.givenName | José | |
| person.identifier | R-000-8GD | |
| person.identifier.ciencia-id | 6016-C902-86A9 | |
| person.identifier.orcid | 0000-0001-7902-1207 | |
| person.identifier.rid | L-3370-2014 | |
| person.identifier.scopus-author-id | 55851941311 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
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