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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

In the era of the fourth industrial revolution, several concepts have arisen in parallel with this new revolution, such as predictive maintenance, which today plays a key role in sustainable manufacturing and production systems by introducing a digital version of machine maintenance. The data extracted from production processes have increased exponentially due to the proliferation of sensing technologies. Even if Maintenance 4.0 faces organizational, financial, or even data source and machine repair challenges, it remains a strong point for the companies that use it. Indeed, it allows for minimizing machine downtime and associated costs, maximizing the life cycle of the machine, and improving the quality and cadence of production. This approach is generally characterized by a very precise workflow, starting with project understanding and data collection and ending with the decision-making phase. This paper presents an exhaustive literature review of methods and applied tools for intelligent predictive maintenance models in Industry 4.0 by identifying and categorizing the life cycle of maintenance projects and the challenges encountered, and presents the models associated with this type of maintenance: condition-based maintenance (CBM), prognostics and health management (PHM), and remaining useful life (RUL). Finally, a novel applied industrial workflow of predictive maintenance is presented including the decision support phase wherein a recommendation for a predictive maintenance platform is presented. This platform ensures the management and fluid data communication between equipment throughout their life cycle in the context of smart maintenance.

Details

Title
On Predictive Maintenance in Industry 4.0: Overview, Models, and Challenges
Author
Achouch, Mounia 1 ; Dimitrova, Mariya 2 ; Ziane, Khaled 3   VIAFID ORCID Logo  ; Sasan Sattarpanah Karganroudi 4   VIAFID ORCID Logo  ; Dhouib, Rizck 2   VIAFID ORCID Logo  ; Ibrahim, Hussein 5 ; Adda, Mehdi 6   VIAFID ORCID Logo 

 Institut Technologique de Maintenance Industrielle ITMI, 175 rue de la Vérendrye, Sept-Îles, QC G4R 5B7, Canada; Département de Mathématique, Informatique et Génie, Université du Québec à Rimouski, Rimouski, QC G56 3A1, Canada; Centre de Recherche et D’innovation en Intelligence Énergétique CR2Ie, 175 rue de la Vérendrye, Sept-Îles, QC G4R 5B7, Canada 
 Institut Technologique de Maintenance Industrielle ITMI, 175 rue de la Vérendrye, Sept-Îles, QC G4R 5B7, Canada 
 Centre de Recherche et D’innovation en Intelligence Énergétique CR2Ie, 175 rue de la Vérendrye, Sept-Îles, QC G4R 5B7, Canada 
 Institut Technologique de Maintenance Industrielle ITMI, 175 rue de la Vérendrye, Sept-Îles, QC G4R 5B7, Canada; Department of Mechanical Engineering, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada 
 Institut Technologique de Maintenance Industrielle ITMI, 175 rue de la Vérendrye, Sept-Îles, QC G4R 5B7, Canada; Centre de Recherche et D’innovation en Intelligence Énergétique CR2Ie, 175 rue de la Vérendrye, Sept-Îles, QC G4R 5B7, Canada 
 Département de Mathématique, Informatique et Génie, Université du Québec à Rimouski, Rimouski, QC G56 3A1, Canada 
First page
8081
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
20763417
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2706109314
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.