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Resilience-driven maintenance scheduling methodology for multi-agent production line system
Wang X(王潇); Qi C(祁超); Wang HW(王洪伟); Si QM(佀庆民); Zhang GW(张国伟)
作者部门机器人学研究室
会议名称27th Chinese Control and Decision Conference, CCDC 2015
会议日期May 23-25, 2015
会议地点Qingdao, China
会议录名称Proceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码614-619
收录类别EI ; CPCI(ISTP)
EI收录号20154401482246
WOS记录号WOS:000375232901036
产权排序3
ISBN号978-1-4799-7016-2
关键词Resilience Deteriorating Quality States Semi-markov Decision Processes Resource Constraints Multi-agent Reinforcement Learning
摘要In recent years, the public has been paying ever greater attention to problems related to resilience, since resilience presents the recovery ability to increasing complexity and vulnerability of disturbances. Many researches have been performed to address resilience of networks disruptions in manufacturing. However, a systematic method to model and analyze maintenance scheduling in disturbed production line system is not well developed. This paper considers a resilience-driven maintenance scheduling methodology under maintenance resource constraints for a simplified production line system, which consists of an upstream production machine, a downstream production machine and an intermediate buffer. The machines with degradation quality states represented by multiple decreasing yield levels are modeled as semi-Markov decision processes. A hierarchical and policy-coupled methodology based on reinforcement learning is used to determine maintenance policy of the system. The numerical results show that the application of the methodology to the aforementioned system can minimize the total cost and converge to the approximate optimal solution.
语种英语
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被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17196
专题机器人学研究室
作者单位1.College of Safety Engineering, Shenyang Aerospace University, Shenyang, China
2.Institute of Systems Engineering, Huazhong University of Science and Technology, Wuhan, China
3.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
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Wang X,Qi C,Wang HW,et al. Resilience-driven maintenance scheduling methodology for multi-agent production line system[C]. Piscataway, NJ, USA:IEEE,2015:614-619.
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