Maintenance strategy for stochastic selective maintenance of a two-state system

2016 ◽  
Vol 11 (4) ◽  
pp. 302 ◽  
Author(s):  
Jing Zhao ◽  
Jian Chao Zeng
Keyword(s):  
State System ◽  
Maintenance Strategy ◽  
Selective Maintenance

scholarly journals Selective Maintenance Optimization for a Multi-State System Considering Human Reliability

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 652 ◽  
Author(s):  
Zhonghao Zhao ◽  
Boping Xiao ◽  
Naichao Wang ◽  
Xiaoyuan Yan ◽  
Lin Ma
Keyword(s):  
Human Error ◽  
The State ◽  
State System ◽  
Maintenance Scheduling ◽  
Discrete Mathematics ◽  
Military Operations ◽  
Maintenance Policy ◽  
Human Reliability ◽  
Selective Maintenance ◽  
Distribution Of Components

In an actual industrial or military operations environment, a multi-state system (MSS) consisting of multi-state components often needs to perform multiple missions in succession. To improve the probability of the system successfully completing the next mission, all the maintenance activities need to be performed during maintenance breaks between any two consecutive missions under limited maintenance resources. In such case, selective maintenance is a widely used maintenance policy. As a typical discrete mathematics problem, selective maintenance has received widespread attention. In this work, a selective maintenance model considering human reliability for multi-component systems is investigated. Each maintenance worker can be in one of multiple discrete working levels due to their human error probability (HEP). The state of components after maintenance is assumed to be random and follow an identified probability distribution. To solve the problem, this paper proposes a human reliability model and a method to determine the state distribution of components after maintenance. The objective of selective maintenance scheduling is to find the maintenance action with the optimal reliability for each component in a maintenance break subject to constraints of time and cost. In place of an enumerative method, a genetic algorithm (GA) is employed to solve the complicated optimization problem taking human reliability into account. The results show the importance of considering human reliability in selective maintenance scheduling for an MSS.

A high‐performance maintenance strategy for stochastic selective maintenance

2018 ◽  
Vol 31 (12) ◽  
Author(s):  
Jing Zhao ◽  
Jianqi Liu ◽  
Zhenting Zhao ◽  
Miao Xin ◽  
Yu Chen
Keyword(s):  
High Performance ◽  
Maintenance Strategy ◽  
Selective Maintenance

scholarly journals Selective Maintenance Optimization for a Multi-State System With Degradation Interaction

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 99191-99206 ◽  
Author(s):  
Zhonghao Zhao ◽  
Boping Xiao ◽  
Naichao Wang ◽  
Xiaoyuan Yan ◽  
Lin Ma
Keyword(s):  
State System ◽  
Maintenance Optimization ◽  
Selective Maintenance

Reliability analysis and selective maintenance for multistate queueing system

2021 ◽  
pp. 1748006X2110343
Author(s):  
Tang Tang ◽  
Lijuan Jia ◽  
Jin Hu ◽  
Yue Wang ◽  
Cheng Ma
Keyword(s):  
Queueing System ◽  
Operation Time ◽  
State System ◽  
Profit Rate ◽  
Time Service ◽  
Queueing Process ◽  
System A ◽  
Binary State ◽  
Deterioration Process ◽  
Selective Maintenance

The reliability theory of the multi-state system (MSS) has received considerable attention in recent years, as it is able to characterize the multi-state property and complicated deterioration process of systems in a finer way than that of binary-state system. In general, the performance of the task processing type MSS is typically measured by an operation time (processing speed). Whereas, considering the queueing phenomenon caused by the random arrival and processing of tasks, some other criteria should be taken into account to evaluate the quality of service (QoS) and the profit of stakeholders, such as waiting time, service and abandon rate of tasks and consequent profit rate. In this article, we focus on the queueing process of tasks and analyse the performance and reliability of MSS in an M/M/2 queueing model, which is referred to as a multi-state queueing system (MSQS). Two kinds of deterioration are studied including the gradual degradation of servers and the sudden breakdown of the whole system. A performance assessment function is defined to obtain the profit rate of MSQS in different performance states. Based on the proposed performance function, the selective maintenance method is studied to optimize the accumulated profit under the constraint of maintenance resource and time.

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