Asset Management, Reliability and Prognostics Modeling Techniques

Mathieu Payette () and Georges Abdul-Nour
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Mathieu Payette: Department of Industrial Engineering, University of Quebec in Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada
Georges Abdul-Nour: Department of Industrial Engineering, University of Quebec in Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada

Sustainability, 2023, vol. 15, issue 9, 1-16

Abstract: In recent years, reliability engineering has seen significant growth in data-driven modeling, mainly due to the democratization of sensing technologies, big data processing, and computing capabilities. It has also seen a paradigm shift, with Engineering of Asset Management (EAM) becoming widely accepted as a high-level framework to support corporate policies and strategies. The rapid evolution of research leads to the development of multiple research communities, making it difficult for the uninitiated to navigate the literature. Indeed, system reliability encompasses several research subfields that focus on maximizing the life cycle of assets, including Reliability, Availability, Maintainability, and Safety (RAMS), Prognostics and Health Management (PHM), and Engineering of Asset Management. This article proposes a review of these concepts with the aim of identifying the different scientific communities, what differentiates them, and what connects them. It also addresses RAMS and PHM modeling techniques and highlights the significance of these disciplines in ensuring the functioning of complex systems. In summary, this article aims to clarify the interrelationship between the topics of reliability engineering, to simplify the search and selection for modeling methods.

Keywords: engineering of asset management; prognostic and health management; reliability; modeling (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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