Selective maintenance model for mission-oriented systems considering heterogeneous missions and budget constraints

2018 ◽  
Author(s):  
L Ribeiro ◽  
C.A.V. Cavalcante
Keyword(s):  
Budget Constraints ◽  
Selective Maintenance ◽  
Maintenance Model

Selective maintenance of multi-state series systems considering maintenance quality uncertainty and failure effects

2021 ◽  
pp. 095440892199693
Author(s):  
Xinlong Li ◽  
Yan Ran ◽  
Genbao Zhang ◽  
Hui Yu
Keyword(s):  
Decision Maker ◽  
Engineering Practice ◽  
Quality Uncertainty ◽  
Equipment Operation ◽  
System Maintenance ◽  
Selective Maintenance ◽  
Maintenance Decision ◽  
Series Systems ◽  
Maintenance Model

In order to improve the lifetime and reliability of equipment operation stage, it is necessary to carry out maintenance for components. The typical selective maintenance model does not consider the maintenance quality uncertainty and the failure effects, which may make the decision-maker overestimates the reliability of completing the next task after system maintenance, resulting in incorrect maintenance decision and prone to serious consequences of failure. In this paper, the potential discrepancy between the target maintenance quality and the actual maintenance quality of the decision maker is considered. At the same time, a multi-state FMECA is proposed to measure the failure effects under different states. Finally, the selective maintenance model of the multi-state series systems is established and solved by the genetic algorithm. The results show that considering the effect of component failure and the uncertainty of maintenance quality has an influence on maintenance decision. The maintenance decision made in this way is more consistent with the engineering practice.

Selective maintenance optimization for random phased-mission systems subject to random common cause failures

2018 ◽  
Vol 233 (3) ◽  
pp. 379-400 ◽  
Author(s):  
Xisheng Jia ◽  
Wenbin Cao ◽  
Qiwei Hu
Keyword(s):  
Single Phase ◽  
Failure Behavior ◽  
Maintenance Optimization ◽  
Simulation Approach ◽  
Common Cause ◽  
Proposed Model ◽  
Common Cause Failures ◽  
Selective Maintenance ◽  
Mission System ◽  
Maintenance Model

In both industrial and military fields, there is such a kind of complicated system termed as phased-mission system, which executes missions composed of several different phases in sequence. The structure, failure behavior, and working conditions of such a system may change from phase to phase. The duration of each phase of such a system involved is random and follows a probability distribution, and the system may suffer some events resulting in simultaneous failures of different elements with different probabilities. In order to guarantee such a system completes the phased-mission successfully, a selective maintenance model for random phased-mission systems subject to random common cause failures is proposed to optimally identify a subset of maintenance activities to be performed on some elements of the system. Thereinto, a novel analytic model is developed to estimate the probability of the maintained random phased-mission system successfully completing the phased-mission, and we compare it with a well-known Monte Carlo Simulation approach. Finally, the proposed selective maintenance model has been successfully applied to an artillery weapon system. Comparative analysis is carried out to compare the proposed model with the traditional ones, including selective maintenance models for deterministic phased-mission systems and deterministic single-phase mission systems. The results show that ignoring some mission properties (e.g. randomness and multiple phases) in selective maintenance optimization will lead to (1) incorrect system and mission modeling, (2) incorrect computation of the probability of the random phased-mission system successfully completing a mission, and/or (3) nonoptimal selective maintenance options.

scholarly journals Optimal Selective Maintenance Decision-Making for Consecutive-Mission Systems with Variable Durations and Limited Maintenance Time

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Huiying Gao ◽  
Xiaoqiang Zhang ◽  
Xiaoqiang Yang ◽  
Bo Zheng
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Great Influence ◽  
Maintenance Strategy ◽  
Maintenance Time ◽  
Selective Maintenance ◽  
Maintenance Decision ◽  
Set Up ◽  
Maintenance Model ◽  
Repairable Components

Maintenance is inevitable for repairable components or systems in modern industries. Since the maintenance effectiveness has a great influence on the subsequent operations and in addition, different maintenance options are possible for the components of the system during the break between any two successive missions, the optimal selective maintenance strategy needs to be determined for a system performing successive missions. A number of selective maintenance models were set up on the basis that the durations of each mission are predetermined, the maintenance time is negligible, and the states of the components at the end of the previous mission can be accurately obtained. However, in the actual industrial and military missions, these premises may not always hold. In this paper, a novel selective maintenance model under uncertainties and limited maintenance time is proposed to improve these deficiencies. The genetic algorithm is selected to solve the optimization problem, and an illustrative example is presented to demonstrate the proposed method. The optimal selective maintenance decision without the constraint of maintenance time is used for comparison.

Selective maintenance optimisation considering random common cause failures and imperfect maintenance

2018 ◽  
Vol 233 (3) ◽  
pp. 427-443
Author(s):  
Wenbin Cao ◽  
Xisheng Jia ◽  
Yu Liu ◽  
Qiwei Hu ◽  
Jianmin Zhao
Keyword(s):  
System Reliability ◽  
Simulation Method ◽  
Imperfect Maintenance ◽  
Common Cause ◽  
System A ◽  
Proposed Model ◽  
Common Cause Failures ◽  
Maintenance Decisions ◽  
Selective Maintenance ◽  
Maintenance Model

This article addresses a selective maintenance optimisation problem for systems subject to random common cause failures. A system is likely to suffer from several random common cause failures during a given mission. Random common cause events, which occur with a specific probability distribution, may result in the simultaneous failures of multiple elements. Because time is one of the most crucial maintenance resources, a time-based imperfect maintenance model is proposed to quantify the maintenance efficiency of each candidate maintenance action. To meet the demands of the next mission, a selective maintenance model is proposed to optimally identify a subset of maintenance activities to be performed on certain elements of a system. A genetic algorithm and Monte Carlo simulation method is presented to solve the proposed selective maintenance optimisation problem. Illustrative examples combined with detailed discussions are presented to demonstrate the effectiveness of the proposed model. The results show that the proposal of time-based imperfect maintenance model can yield better maintenance results, while ignoring random common cause failures in selective maintenance optimisation may produce biased maintenance decisions and system reliability.

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