A systematic decision-making approach for the optimal product-service system planning

Authors:
Xiuli Geng;Xuening Chu;Deyi Xue;Zaifang Zhang
Affiliations:
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China;School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China;Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4;School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Product-service system (PSS) planning has been attracting attentions of global manufacturers to change from providing only products to offering both products and their services as a whole. The PSS planning approach can maintain the functionality of products for customers throughout the whole product life-cycle. Identification of the product and service parameters in early design stages plays a critical role in PSS development. The PSS planning is usually started by the mapping from customer requirements (CRs) in the customer domain to engineering characteristics (ECs), including product-related ECs (P-ECs) and service-related ECs (S-ECs), in the functional domain. In this paper, a systematic decision-making approach for PSS planning is developed to determine the optimal fulfillment levels of ECs considering requirements of customers and manufacturers. The PSS planning is conducted through four phases. First, the initial weights of ECs considering customer needs are achieved based on fuzzy pairwise comparison. Second, the data envelopment analysis (DEA) approach is applied to obtain the final weights of ECs considering customer requirements as well as other requirements of the manufacturers. Third, the ECs are categorized into different Kano attribute classes using fuzzy Kano's questionnaire (FKQ) and fuzzy Kano's mode (FKM) for evaluation of the PSS. In the last phase, non-linear programming is carried out to maximize the fulfillment levels of ECs. A case study is carried out to demonstrate the effectiveness of the developed optimal PSS planning approach.