Name
Abstract | ||
|---|---|---|
In this paper, a novel predictive maintenance policy with multi-level decision-making is proposed for multi-component system with complex structure. The main idea is to propose a decision-making process considered on two levels: system level and component one. The goal of the decision rules at the system level is to address if preventive maintenance actions are needed regarding the predictive reliability of the system. At component level the decision rules aim at identifying optimally a group of several components to be preventively maintained when preventive maintenance is trigged due to the system level decision. Selecting optimal components is based on a cost-based group improvement factor taking into account the predictive reliability of the components, the economic dependencies as well as the location of the components in the system. Moreover, a cost model is developed to find the optimal maintenance decision variables. A 14-component system is finally introduced to illustrate the use and the performance of the proposed predictive maintenance policy. Different sensitivity analysis are also investigated and discussed. Indeed, the proposed policy provides more flexibility in maintenance decision-making for complex structure systems, hence leading to significant profits in terms of maintenance cost when compared with existing policies. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.ress.2015.07.017 | Reliability Engineering & System Safety |
Keywords | Field | DocType |
Multi-component system,Condition-based maintenance,Opportunistic,Economic dependencies,Prognostic,Importance measure | Decision rule,Decision variables,Condition-based maintenance,Engineering,Optimal maintenance,Predictive maintenance,Reliability engineering,Preventive maintenance,Profit (economics),System level | Journal |
Volume | ISSN | Citations |
144 | 0951-8320 | 21 |
PageRank | References | Authors |
0.84 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kim-Anh Nguyen | 1 | 25 | 1.31 |
| Phuc Do | 2 | 33 | 4.48 |
| Antoine Grall | 3 | 117 | 15.26 |