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Showing 6 results for Parallel System
Ebrahim Amini-Seresht, Majid Sadeghifar, Mona Shiri,
Volume 12, Issue 1 (9-2018)
Abstract
In this paper, we further investigate stochastic comparisons of the lifetime of parallel systems with heterogeneous independent Pareto components in term of the star order and convex order. It will be proved that the lifetime of a parallel system with heterogeneous independent components from Pareto model is always smaller than from the lifetime of another parallel system with homogeneous independent components from Pareto model in the sense of convex order. Also, under a general condition on the scale parameters, it is proved a result involving with star order.
Reza Ahmadi,
Volume 14, Issue 1 (8-2020)
Abstract
We propose an integrated approach for decision making about repair and maintenance of deteriorating systems whose failures are detected only by inspections. Inspections at periodic times reveal the true state of the system's components and preventive and corrective maintenance actions are carried out in response to the observed system state. Assuming a threshold-type policy, the paper aims at minimizing the long-run average maintenance cost per unit time by determining appropriate inspection intervals and a maintenance threshold. Using the renewal reward theorem, the expected cost per cycle and expected cycle length emerge as solutions of equations, and a recursive scheme is devised to solve them. We demonstrate the procedure and its outperformance over specific cases when the components' lifetime conforms to a Weibull distribution. Further, a sensitivity analysis is performed to determine the impact of the model's parameters. Attention has turned to perfect repair and inspection, but the structure allows different scenarios to be explored.
Elham Basiri,
Volume 14, Issue 2 (2-2021)
Abstract
When a system is used, it is often of interest to determine with what probability it will work longer than a pre-fixed time. In other words, determining the reliability of this system is of interest. On the other hand, the reliability of each system depends on the structure and reliability of its components. Therefore, in order to improve the reliability of the system, the reliability of its components should be improved. For this purpose, it is necessary to carry out maintenance operations, which will increase costs. Another way to increase the reliability of systems is to change the location of the components. In this paper, the location of system components and optimal maintenance period are determined by minimizing the costs and maximizing the reliability of a series-parallel system. Finally, a numerical example is presented to evaluate the results in the paper.
Ebrahim Amini Seresht, Ghobad Barmalzan,
Volume 15, Issue 2 (3-2022)
Abstract
This paper discusses stochastic comparisons of the parallel and series systems comprising multiple-outlier scale components. Under uncertain conditions on the baseline reversed hazard rate, hazard rate functions and scale parameters, the likelihood ratio, dispersive and mean residual life orders between parallel and series systems are established. We then apply the results for two exceptional cases of the multiple-outlier scale model: gamma and Pareto multiple-outlier components to illustrate the found results.
Abedin Haidari, Mostafa Sattari, Ghobad Barmalzan,
Volume 16, Issue 1 (9-2022)
Abstract
Consider two parallel systems with their component lifetimes following a generalized exponential distribution. In this paper, we introduce a region based on existing shape and scale parameters included in the distribution of one of the systems. If another parallel system's vector of scale parameters lies in that region, then the likelihood ratio ordering between the two systems holds. An extension of this result to the case when the lifetimes of components follow exponentiated Weibull distribution is also presented.
Aqeel Lazam Razzaq, Isaac Almasi, Ghobad Saadat Kia,
Volume 18, Issue 2 (2-2025)
Abstract
Adding parameters to a known distribution is a valuable way of constructing flexible families of distributions. In this paper, we introduce a new model, the modified additive hazard rate model, by replacing the additive hazard rate distribution in the general proportional add ratio model. Next, when two sets of random variables follow the modified additive hazard model, we establish stochastic comparisons between the series and parallel systems comprising these components.
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