A Study on the Impacts of Maintenance Duration on Dynamic Grouping Modeling and Optimization of Multicomponent Systems

Abstract

In the framework of maintenance optimization of multi-component systems, dynamic grouping maintenance based on rolling horizon has developed and becomes an interesting approach. However, most existing dynamic grouping models assume that the maintenance duration is negligible. This assumption may be not always relevant and limits the application of these models in many real situations. The first objective of this paper is to develop a dynamic grouping model in presence of both corrective and preventive maintenance duration for complex structure systems. A new practical maintenance cost model is proposed allowing to take into consideration of maintenance duration and system structure as well as economic dependence between components. Taking into maintenance duration and system structure leads however to a complex grouping model which is efficiently solved by proposed analytical methods. The second objective is to investigate the impacts of maintenance duration on grouping modeling and grouping optimization. Both theoretical and experimental studies give a complete vision about maintenance duration impacts and some recommendations in real applications. The uses and advantages of the proposed grouping maintenance approach are illustrated through a numerical example of a six-component system.

Standardising Maintenance Jobs to Improve Grouping Decision Making

“…Other methods suggest evaluating the condition before deciding whether to do opportunistic maintenance (Hu and Zhang, 2014;Poppe et al, 2018) or grouping based on a predetermined replacement threshold and replacing all if one fails (Dekker and Smeitink, 1991;Wu et al, 2020). Other grouping methods suggest optimizing the maintenance plans for the individual pieces of equipment and then grouping based on shared intervals (Van et al, 2013;Vu et al, 2018). Li et al (2018) suggest grouping production equipment maintenance by the criticality of the machines.…”

“…That is, a situation where some of the knowledge required to make the decision is tacit and thus cannot be represented by data in an algorithm or other computerised methods. As shown in the literature review, several methods have been proposed for the clustering of maintenance (Assaf and Shanthikumar, 1987;Cui and Li, 2006;Dekker and Smeitink, 1991;Hu and Zhang, 2014;Li et al, 2018;Nzukam et al, 2017;Poppe et al, 2018;Van et al, 2013;Vu et al, 2014Vu et al, , 2018Wu et al, 2020;Zhang et al, 2017). However, these methods tend to not account for imperfect and unavailable data.…”

“…Grouping methods have been suggested in both manufacturing and maintenance literature. These methods are most commonly focused on algorithms that analyse the maintenance and suggest optimized solutions (Assaf and Shanthikumar, 1987;Cui and Li, 2006;Dekker and Smeitink, 1991;Hu and Zhang, 2014;Li et al, 2018;Navaei and ElMaraghy, 2014;Nzukam et al, 2017;Poppe et al, 2018; Van et al, 2013;Vu et al, 2018Vu et al, , 2014Wu et al, 2020;Zhang et al, 2017). However, the articles have not focused on creating methods and frameworks for more complex decisions that require human expert evaluation.…”

A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation

“…1. Note that the system age used in this paper follows the literature on imperfect maintenance [32]- [34].…”

Maintenance optimisation for systems with multi-dimensional degradation and imperfect inspections

“…Maintenance operation is an effective tool to improve the production quality and reduce economic losses due to system failures. Traditionally, failure data are usually used to establish reliability models, based on which maintenance decisions are made (Zhao et al, 2018;Vu et al, 2018;Wu et al, 2016;Finkelstein et al, 2016;Gao et al, 2019;Qin and Li, 2020). Recently, however, as a result of the improved quality and reliability of systems, it is becoming increasingly more difficult to obtain the failure data, which frustrates failure-model based reliability analysis and the associated maintenance strategies.…”