Selection of design alternatives for smart product service system: A rough-fuzzy data envelopment analysis approach

Abstract

The rapid development and application of smart technologies have trigged manufacturers’ servitization towards a new paradigm − smart product service system (PSS). Accurate selection of design alternatives are significantly vital to successful development project of smart PSS. This study establishes a new criteria system considering the value symbiosis among stakeholders and the smart capabilities generated using smart technologies. Since the proposed criteria system incorporates two types of criteria: cost-based and benefit-based, data envelopment analysis (DEA) method is more suitable for alternatives evaluation over other methods by requiring less information, fitting multiple data scales and not needing criteria weights. However, the previously developed DEA methods rarely simultaneously consider the intrapersonal linguistic vagueness and interpersonal preference randomness inherently involved in the selection process, which may lead to inaccurate and distorted results. Therefore, this study proposes a novel rough-fuzzy DEA method to select the suitable smart PSS design alternatives, integrating the strength of fuzzy number in capturing intrapersonal uncertainty and the feasibility of rough number in perceiving the interpersonal uncertainty. Finally, the validity and effectiveness of the proposed approach are demonstrated through a case study of smart conditioner service system and its comparisons with other methods.