A service-oriented multi-player maintenance grouping strategy for complex multi-component system based on game theory

• Published in: Advanced engineering informatics Vol. 42; p. 100970
• Main Authors: Chang, Fengtian, Zhou, Guanghui, Cheng, Wei, Zhang, Chao, Tian, Changle
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2019
• Subjects: Maintenance grouping strategy; Performance-based maintenance; Proactive services; Smart product service system; Stackelberg-Nash game; Smart product service system; Performance-based maintenance; Maintenance grouping strategy; Stackelberg-Nash game; Proactive services
• ISSN: 1474-0346
• DOI: 10.1016/j.aei.2019.100970

•A service-oriented multi-player maintenance grouping strategy is proposed.•The interaction relations among one OEM and multiply service providers are modeled.•A multi-objective Stackelberg-Nash game is constructed.•NSGA-II and GA are used to solve the bi-level joint optimization model.•The grouping strategies implement the value increment for each proactive exactor. The development of smart product service system (PSS) urges the emergence of service-oriented maintenance grouping strategy for complex multi-component system. This strategy is designed from the data-driven performance-based service manner where the proactive original equipment manufacturer (OEM) and service providers are both involved. In this situation, the traditional maintenance grouping methods are incapable to determine the optimal grouping service time for each exactor due to the little consideration from their interaction relations in the grouping process. Thus, this paper proposes one OEM and multiple service provider’s multi-player maintenance grouping strategy. It is constructed from the multi-objective Stackelberg-Nash game model where the OEM is the upper-level leader and all the involved service providers are the lower-level followers. The serviced components, service time and paid prices are considered firstly by the leader. After that, the followers could compete to select the remaining serviced components and service time. In order to obtain the Stackelberg-Nash equilibrium solution, the bi-level nested parallel solution algorithm with the improved multi-fitness functions is also developed. Finally, a numerical example from wind turbine is studied. The evaluation and comparison results show that our method could provide a feasible and effective maintenance grouping strategy for each player under smart PSS.