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ABSTRACT
In this paper, a cold standby repairable system consisting of two dissimilar components and one repairman is studied. Assume that Component 2 after repair is ‘as good as new’ while Component 1 after repair is not, but Component 1 has priority in use and repair. Under these assumptions, using a geometric process, we consider a replacement policy based on Component 1 age T as the system age under which the cold standby system is replaced when the system age reaches T. Our problem is to determine an optimal replacement policy T* such that the average cost rate of the system is minimised. The explicit expression of the average cost rate is derived, the corresponding optimal replacement policy T* can be determined analytically or numerically. Finally, a numerical example is given to illustrate the model developed, and some sensitivity analysis on the optimal solution is also conducted.
Acknowledgments
The authors are grateful for the Editor's and the referee's valuable comments and suggestions, which have considerably improved the presentation of the paper.
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No potential conflict of interest was reported by the authors.
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Notes on contributors
Yuan Lin Zhang
Yuan Lin Zhang is a professor with the Department of Mathematics, Southeast University. His research interests include applied probability, stochastic operations research, and Insurance mathematics and risk theory. He has published five books, and more than 100 articles in Applied Mathematics and Computation, Applied Mathematical Modelling, Computers and Industrial Engineering, Computers and Mathematics with Applications, Computers and Operations Research, European Journal of Operational Research, Engineering Optimization, IEEE Transactions on Reliability, International Journal of Systems Science, Journal of Applied Probability, Journal of Engineering Manufacture, Journal of the Operational Research Society, Microelectronics and Reliability, Naval Research Logistics, Reliability Engineering and System Safety and others. He is a fellow of the Royal Statistical Society of the UK, and a member of the Institute of Mathematical Statistics of USA.
Guan Jun Wang
Guan Jun Wang is a professor and doctoral tutor with the Department of Mathematics, Southeast University. He graduated in mathematics from LanZhou University in 1999, earned the master degree, and is assiduously studying for a doctor's degree. His research interests in applied probability, and stochastic operations research. He has published some articles in International Journal of Systems Science, IEEE Transactions on Reliability, European Journal of Operational Research, Engineering Optimization, Computers and Mathematics with Applications, Applied Mathematical Modelling, Computers & Industrial Engineering and others.