Abstract
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.
Highlights
Manufacturing industries are experiencing a transition of value creation patterns from the design and production of products to the design and the delivery of services based on products, to accommodate increasingly global competition and customer-centered business settings [1]
Services, and resources were mapped as different layers in a product–service systems (PSS) multilayer network
Service activities selection and resource allocation were combined to evaluate the objective functions of solutions systematically and precisely
Summary
Manufacturing industries are experiencing a transition of value creation patterns from the design and production of products to the design and the delivery of services based on products, to accommodate increasingly global competition and customer-centered business settings [1]. It is necessary to combine service activities selection and resource allocation into a whole process during the PSS configuration optimization. Based on the above analysis, it was found that: (a) PSS configuration is an imperative part of PSS design; (b) existing PSS configuration solutions are obtained in the module granularity; and (c) the significant impact of service details on the performance of a PSS configuration solution has not been given sufficient attention in recent research studies. The complex network is chosen as the framework for the PSS modeling because its structural properties enable the exploration of the interactions between products, resources, and service activities. Multilayer networks were proposed to express different types of relationships between one single type of elements in different layers [51,52] They have been used to model other systems, including those with different types of elements.
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