Abstract

Nowadays, along with the development of smart product-service paradigm, the service-oriented complex equipment (SocE) that considers the proactive condition-based maintenance services integration and planning is drawing wide attentions. The traditional integrations focus on the static configuration processes and the dynamic decision-makings are mainly planned from end users. This blocks the smart service transformations for providers, and brings the improper service matching and selections with higher cost, response time or lower service qualities. To bridge this gap, the dynamic multi-layer maintenance service network evolution model and decision-making method are proposed. Firstly, the model focuses on the SocE and builds the dynamic service network. On basis of this network, the data-driven network evolution processes, evolution mechanisms and modeling flows are developed to fulfill the dynamic configuration, and thus to form the SocE. Secondly, combining with these configurated feasible services, the dynamic decision-making that considers activities and providers selections is developed with the network node characteristics. Finally, the experimental simulation and application cases are both displayed and discussed. It shows the feasibility and effectiveness of the proposed model and method.

Full Text
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