An integrated approach for selecting design parameters in smart product-service system conceptual design

Nowadays, with the rapid development of cyber physical systems, IoT, and artificial intelligence, more and more attention has been paid to adapting the combination of smart, connected products and their generated services. Among these, smart product-service system (SPSS) with the unique features of smartness, connection, value co-creation, and data-driven has been widely concerned. Therefore, based on axiomatic design theory, the mapping from function domain to physical domain is a critical process in SPSS's conceptual design and the selecting of design parameters in physical domain has great impact on meeting multi-stakeholders' benefits. Nevertheless, despite a few works on requirement conversion, it is not clear about the mapping mechanism under the target of value co-creation. Aiming to fill this gap, an integrated SPSS conceptual design method is proposed to solve the cross-domain mapping problem. It decomposes and reorganizes SPSS's function requirements with requirement development laws in TRIZ and divides the physical domain into product-related domain and service-related domain. Design parameters would be selected and evaluated by domain experts based on fuzzy comprehensive evaluation from different dimensions, which could represent the benefit of multi-stakeholders. Next, a binary integer programming (BIP) model with restrictions from different stakeholders would be constructed, which could be regarded as a multi-objective optimization problem. To solve the BIP model, the genetic algorithm is used and the optimal design parameters combination could be generated as the output of this process. Finally, a case study is carried out to demonstrate the feasibility and advantages of the integrated approach for cross-domain mapping in SPSS conceptual design.