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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)
Department机器人学研究室
Conference Name27th Chinese Control and Decision Conference, CCDC 2015
Conference DateMay 23-25, 2015
Conference PlaceQingdao, China
Source PublicationProceedings of the 2015 27th Chinese Control and Decision Conference, CCDC 2015
PublisherIEEE
Publication PlacePiscataway, NJ, USA
2015
Pages614-619
Indexed ByEI ; CPCI(ISTP)
EI Accession number20154401482246
WOS IDWOS:000375232901036
Contribution Rank3
ISBN978-1-4799-7016-2
KeywordResilience Deteriorating Quality States Semi-markov Decision Processes Resource Constraints Multi-agent Reinforcement Learning
AbstractIn 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.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/17196
Collection机器人学研究室
Affiliation1.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
Recommended Citation
GB/T 7714
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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