Maintenance optimization in industry 4.0

Luca Pinciroli, Piero Baraldi and Enrico Zio

Reliability Engineering and System Safety, 2023, vol. 234, issue C

Abstract: This work reviews maintenance optimization from different and complementary points of view. Specifically, we systematically analyze the knowledge, information and data that can be exploited for maintenance optimization within the Industry 4.0 paradigm. Then, the possible objectives of the optimization are critically discussed, together with the maintenance features to be optimized, such as maintenance periods and degradation thresholds. The main challenges and trends of maintenance optimization are, then, highlighted and the need is identified for methods that do not require a-priori selection of a predefined maintenance strategy, are able to deal with large amounts of heterogeneous data collected from different sources, can properly treat all the uncertainties affecting the behavior of the systems and the environment, and can jointly consider multiple optimization objectives, including the emerging ones related to sustainability and resilience.

Keywords: Maintenance optimization; Industry 4.0; Knowledge information and data; Optimization approaches; Uncertain systems (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:234:y:2023:i:c:s0951832023001199

DOI: 10.1016/j.ress.2023.109204

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