Hypotheses in Opportunistic Maintenance Modeling: A Critical and Systematic Literature Review

Because they account for realistic effects in opportunistic maintenance modeling, dependency hypotheses are extremely diverse in the literature. Despite recent reviews, a clear view of the dependency hypotheses is currently missing in the literature, especially regarding component interactions, resource constraints and human factors. In this paper, we provide a conceptual background on dependence modeling and the notion of maintenance opportunity. Then, a critical systematic literature review, following the PRISMA guidelines, is carried out, focusing on the current hypotheses in opportunistic maintenance, including component interactions, workers’ skills and resource constraints, economic dependence and optimization objectives. The different dependence types are identified and defined, and their presence in the literature is quantified. The included papers in this review (n=91) were selected on the basis of relevance to the research questions from the Web of Science, Scopus and Google Scholar databases. Exclusion criteria were set, related to the year of publication (from 2000) and language (limited to French or English), and inclusion criteria required the paper to cover modeling, simulating or reviewing literature related to opportunistic maintenance with dependencies. The results show that economic dependence is mostly modeled by sharing downtime or set-up costs. The objective function for optimization is mostly found to be the economic cost of maintenance, with concerningly little consideration for environmental indicators. These results are finally discussed in light of advances in predictive analytics and current challenges in the sustainability of industrial processes. Further developments should consider including the social and environmental aspects of sustainability in the dependencies, but also look into the benefits that predictive analytics can bring to opportunistic maintenance. The variety of modeling assumptions and dependences presented in the literature does not always allow comparing the results of the models.

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Publication Details

Journal
Machines
Published
2025-10-14
DOI
https://doi.org/10.3390/machines13100947
Primary Topic
Reliability and Maintenance Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Hypotheses in Opportunistic Maintenance Modeling: A Critical and Systematic Literature Review

Luca Tiberi, Phuc Do, Pierre Dehombreux, Lorenzo Colantonio et al.
Machines
Reliability and Maintenance Optimization
article

Hypotheses in Opportunistic Maintenance Modeling: A Critical and Systematic Literature Review

Luca Tiberi, Phuc Do, Pierre Dehombreux, Lorenzo Colantonio, Benoît Iung, Lucas Equeter
article en

Abstract

Because they account for realistic effects in opportunistic maintenance modeling, dependency hypotheses are extremely diverse in the literature. Despite recent reviews, a clear view of the dependency hypotheses is currently missing in the literature, especially regarding component interactions, resource constraints and human factors. In this paper, we provide a conceptual background on dependence modeling and the notion of maintenance opportunity. Then, a critical systematic literature review, following the PRISMA guidelines, is carried out, focusing on the current hypotheses in opportunistic maintenance, including component interactions, workers’ skills and resource constraints, economic dependence and optimization objectives. The different dependence types are identified and defined, and their presence in the literature is quantified. The included papers in this review (n=91) were selected on the basis of relevance to the research questions from the Web of Science, Scopus and Google Scholar databases. Exclusion criteria were set, related to the year of publication (from 2000) and language (limited to French or English), and inclusion criteria required the paper to cover modeling, simulating or reviewing literature related to opportunistic maintenance with dependencies. The results show that economic dependence is mostly modeled by sharing downtime or set-up costs. The objective function for optimization is mostly found to be the economic cost of maintenance, with concerningly little consideration for environmental indicators. These results are finally discussed in light of advances in predictive analytics and current challenges in the sustainability of industrial processes. Further developments should consider including the social and environmental aspects of sustainability in the dependencies, but also look into the benefits that predictive analytics can bring to opportunistic maintenance. The variety of modeling assumptions and dependences presented in the literature does not always allow comparing the results of the models.

MachinesVol. 13(10)
Centre National de la Recherche Scientifique (FR), University of Mons (BE), Centre de Recherche en Automatique de Nancy (FR), IMT Mines Alès (FR)
Fonds De La Recherche Scientifique - FNRS
Openalex Percentile: Top 64%
Reliability and Maintenance Optimization
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