Preventive maintenance of multistate systems subject to shocks

2015 ◽  
Vol 32 (2) ◽  
pp. 283-291 ◽  
Author(s):  
Maxim Finkelstein ◽  
Ilya Gertsbakh
Keyword(s):  
Preventive Maintenance ◽  
Multistate Systems

scholarly journals Preventive Maintenance Interval Optimization for Continuous Multistate Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Ruiying Li ◽  
Xufeng Zhang
Keyword(s):  
Preventive Maintenance ◽  
Breakdown Rate ◽  
Computer Cluster ◽  
Optimization Framework ◽  
Performance Change ◽  
Cost System ◽  
Binary State ◽  
Multistate Systems ◽  
Complete Failure ◽  
System Breakdown

Preventive maintenance (PM), which is performed periodically on the system to lessen its failing probability, can effectively decrease the loss caused by the system breakdown or the performance degradation. The optimal PM interval has been well studied for both binary-state systems (BSSs) and discrete multistate systems (MSSs). However, in reality, the performance of many systems can change continuously, ranging from complete failure to perfect functioning. Considering such characteristics of systems, two types of performance-based measures, performance availability and probabilistic resilience, are addressed to quantify the system’s behaviour for continuous MSS. A Monte Carlo-based method is given to analyse the performance change process of the system, and an optimization framework is proposed to find the optimal PM interval with the considerations of per-unit-time cost, system breakdown rate, performance availability, and probabilistic resilience. A computer cluster is used as an example to illustrate the effectiveness of our proposed method.

ABOUT IMPROVING THE QUALITY OF PREVENTIVE MAINTENANCE EQUIPMENT FOR PROCESSING FACTORY LLC "SUEK-KHAKASIA"

2017 ◽  
Vol 12 (39) ◽  
pp. 166-172
Author(s):  
I.V. Pivovarov ◽  
◽  
A.A. Lakhin ◽  
I.V. Maryasov ◽  
D.S. Senatorov ◽  
...  
Keyword(s):  
Preventive Maintenance

Optimizing preventive maintenance over a finite planning horizon in a semi-Markov framework

2020 ◽  
Author(s):  
Antonio Sánchez Herguedas ◽  
Adolfo Crespo Márquez ◽  
Francisco Rodrigo Muñoz
Keyword(s):  
Preventive Maintenance ◽  
Recurrence Relations ◽  
Direct Calculation ◽  
Planning Horizon ◽  
Practical Implementation ◽  
Practical Application ◽  
Mathematical Solution ◽  
Accumulated Reward ◽  
Finite Planning Horizon

Abstract This paper describes the optimization of preventive maintenance (PM) over a finite planning horizon in a semi-Markov framework. In this framework, the asset may be operating, and providing income for the asset owner, or not operating and undergoing PM, or not operating and undergoing corrective maintenance following failure. PM is triggered when the asset has been operating for τ time units. A number m of transitions specifies the finite horizon. This system is described with a set of recurrence relations, and their z-transform is used to determine the value of τ that maximizes the average accumulated reward over the horizon. We study under what conditions a solution can be found, and for those specific cases the solution τ* is calculated. Despite the complexity of the mathematical solution, the result obtained allows the analyst to provide a quick and easy-to-use tool for practical application in many real-world cases. To demonstrate this, the method has been implemented for a case study, and its accuracy and practical implementation were tested using Monte Carlo simulation and direct calculation.

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