Product–service systems (PSS) accelerate the transition of value creation patterns for manufacturing industries, from product design and production to the delivery of overall solution integrating products and services. Existing PSS configuration solutions provide customers with preferable product modules and service modules characterized by the module granularity. Every service module is essentially a whole service flow. However, the performance of the PSS configuration solution is greatly influenced by service details. In summary, this paper studied the configuration optimization of product-oriented PSS using a fine-grained perspective. A multilayer network composed of (i) a product layer, (ii) a service layer, and (iii) a resource layer was constructed to represent the elements (product parts, service activities, resources) and relationships in PSS. Service activities selection and resource allocation were considered jointly to construct the mathematical model of PSS configuration optimization, thus enabling the calculation of optimizing objectives (time, cost, and reliability) under constraints closer to the actual implementation. The importance degree of service activity was considered to improve the performance of service activities with higher importance. Corresponding algorithms were improved and applied for obtaining the optimal solutions. The case study in the automotive industry shows the various advantages of the proposed method.
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