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Mean residual lifetime assessment approach for a multi-state standby system
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The Graduate School of Natural and Applied Sciences, Ege University, Turkey
Department of Statistics, Ege University, Turkey
Submission date: 2023-01-25
Final revision date: 2023-04-25
Acceptance date: 2023-05-19
Online publication date: 2023-05-28
Publication date: 2023-05-28
Corresponding author
Funda Iscioglu   

Department of Statistics, Ege University, 35040, Izmir, Turkey
Eksploatacja i Niezawodność – Maintenance and Reliability 2023;25(2):166328
  • The mean residual lifetime functions of a three-state standby system are obtained.
  • In MSS, a performance measures are obtained in case a system is at state "j or above"at t.
  • The main contribution of the study; MRL is obtained when the system is at state "j".
  • The effect of different degradation rates of each state on the MRL is investigated.
  • Optimization problem finds the average replacement costs, the optimal replacement times.
In this paper, a new MRL assessment approach for a multi-state standby system is considered. The three-state system is backed up with a binary cold standby unit. Given that the system is at a specific state at time t, obtaining the MRL is worth considering in conducting the maintenance and repair plans of the system. For different degradation rates and time points, MRL results are examined. An HCTMP is considered for the degradation. Therefore, when the system is observed to be at its perfect state, the MRL decrease with an increase in all the failure rates of the system. However, when the system is observed to be at its partial state, the MRL is not affected by the increase in the failure rate pertained to the perfect state. The MRL when the system has known to be failed before time t and backed up with the standby unit increases with the time increase whereas the MRL when the system is at its perfect(or partial) state is constant when time increases. Moreover, cost evaluation of the system is analyzed. The results are supported with numerical examples and graphical representations.
This research is supported by the Scientific Research Projects Office of Ege University under Grant No.FYL-2020-21761.