The design of a reliable system depends greatly on several key factors, including the allocation of reliability to individual components, the use of redundancy, and the allocation of redundant components to enhance ov...
详细信息
This article presents a new interpretation and formulation of the reliability-redundancyallocation Problem (RRAP) and demonstrates that solutions to this new problem provide distinct advantages compared with traditio...
详细信息
This article presents a new interpretation and formulation of the reliability-redundancyallocation Problem (RRAP) and demonstrates that solutions to this new problem provide distinct advantages compared with traditional approaches. Using redundant components is a common method to increase the reliability of a system. In order to add the redundant components to a system or a subsystem, there are two traditional types of strategies called active and standby redundancy. Recently a new redundancy strategy, called the mixed strategy, has been introduced. It has been proved that in the redundancyallocation Problem (RAP), this new strategy has a better performance compared with active and standby strategies alone. In this article, the recently introduced mixed strategy is implemented in the RRAP, which is more complicated than the RAP, and the results of using the mixed strategy are compared with the active and standby strategies. To analyze the performance of the new approach, some benchmark problems on the RRAP are selected and the mixed strategy is used to optimize the system reliability in these situations. Finally, the reliability of benchmark problems with the mixed strategy is compared with the best results of the systems when active or standby strategies are considered. The final results show that the mixed strategy results in an improvement in the reliability of all the benchmark problems and the new strategy outperforms the active and standby strategies in RRAP.
The reliability-redundancyallocation problem (RRAP) has been widely investigated during the last decade. In most of existing studies, component failures are assumed to be covered perfectly which means all faults can ...
详细信息
ISBN:
(纸本)9781665458139
The reliability-redundancyallocation problem (RRAP) has been widely investigated during the last decade. In most of existing studies, component failures are assumed to be covered perfectly which means all faults can be timely detected, located, and isolated. However, the coverage could be imperfect in reality and a not-covered component failure may lead to system failure without constraint. In this paper, the RRAP is solved considering the imperfect fault coverage model (IFCM, only faulty components can be covered) and the irrelevance coverage model (ICM, both faulty and irrelevant components can be covered). It has been proved that an excessive level of redundancy may reduce the system reliability rather than improve it when the fault coverage is imperfect. Therefore, when the IFCM and the ICM are considered in the RRAP, in addition to resource constraints, the coverage model itself also limits the level of redundancy. Three benchmark problems are investigated in this paper. The genetic algorithm is adopted to solve the new mixed integer nonlinear programming problem. The results show that the optimal designs of system in the two coverage models are different from the existing researches that only consider the perfect fault coverage model. The redundant components used in the optimal solution are less than the existing studies. The advantage of the ICM over the IFCM is also verified in this paper.
暂无评论