Analysis and optimization of a joint redundancy and inspection-based maintenance strategy
He, Pan; Liu, Gang; Tan, Chun; Yuan, Yue
2016
会议日期November 3, 2016 - November 5, 2016
会议地点Kunming, Yunnan, China
DOI10.1007/978-981-10-3482-4_7
页码94-108
通讯作者He, Pan (hepan@cigit.ac.cn)
英文摘要While joint redundancy and maintenance strategies are used to maintain system reliability, optimization is often conducted to choose appropriate configuration parameters for each strategy. Existing research mainly deals with imperfect preventive maintenance strategy optimization and ignores the impact of inspection and detection interval before maintenance occurs. So, this paper aims at a joint redundancy and inspection-based maintenance strategy which is widely used in computing systems. Following the existing Markov-chain based evaluation method, an optimization model is built to choose appropriate redundancy for system structure and inspection interval for maintenance. This model is constructed to achieve best system performance under certain reliability constraint, whereas the reliability and performance models are built according to component redundancy and inspection interval. Since there is no closed-form formula of this optimization model, a greedy iterative search algorithm is used to get optimal solutions for inspection rate under each redundancy value. Empirical studies show the process of building the optimization model and calculating the optimal parameters from the model. The results indicate that this optimization method could find optimal redundancy as well as inspection rate. © Springer Nature Singapore Pte Ltd. 2016.
会议录15th National Software Application Conference, NASAC 2016
语种英语
ISSN号18650929
内容类型会议论文
源URL[http://119.78.100.138/handle/2HOD01W0/4676]  
专题北斗导航工程中心
作者单位Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China
推荐引用方式
GB/T 7714
He, Pan,Liu, Gang,Tan, Chun,et al. Analysis and optimization of a joint redundancy and inspection-based maintenance strategy[C]. 见:. Kunming, Yunnan, China. November 3, 2016 - November 5, 2016.
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