A scenario-driven sustainable product and service system design for elderly nursing based on QFD

被引:4
|
作者
Geng, Xiuli [1 ,2 ]
Li, Yiqun [1 ]
Wang, Duojin [3 ,4 ]
Zhou, Qingchao [1 ]
机构
[1] Univ Shanghai Sci & Technol, Business Sch, Jungong Rd 516, Shanghai 200093, Peoples R China
[2] Univ Shanghai Sci & Technol, Sch Intelligent Emergency Management, Jungong Rd 516, Shanghai 200093, Peoples R China
[3] Univ Shanghai Sci & Technol, Inst Intelligent Rehabil Engn & Technol, Jungong Rd 516, Shanghai 200093, Peoples R China
[4] Shanghai Engn Res Ctr Assist Devices, Jungong Rd 516, Shanghai 200093, Peoples R China
关键词
Aging population; Product -service system; Quality function deployment; Link prediction; DeepWalk; Random walk with restart; TODIM; Nash bargaining; MODEL;
D O I
10.1016/j.aei.2024.102368
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The issue of increasingly aging population has created an increased demand for nursing beds, which not only in terms of quantity but also functionality. Product -service system (PSS) is a highly integrated production system of products and services which can afford full life cycle product and service solutions. This paper introduces a nursing bed PSS, which is able to provide sustainable functional solutions for product design guided by customer requirements. Quality function deployment (QFD) is a common method for requirement -driven solution design, which can transform requirement attributes (RAs) into engineering characteristics (ECs). Nevertheless, general QFD requirement acquisition exists limitations, such as the subjectivity and incomprehensiveness of expert evaluations. Besides, the psychological preference of decision makers to deal with risk is ignored. In this study, we propose a scenario -driven dual -layer requirement network and a modified QFD model to mine latent RAs and prioritize the ECs by maximizing customer satisfaction using Nash Bargaining. The major contributions are listed as follows. First, nursing scenarios drive the acquisition of multiple stakeholders. Second, link prediction program is employed to map and mine latent RAs. Third, TODIM is applied in order to consider the psychological references of decision makers. Fourth, a Nash bargaining non-linear programming model is constructed for optimal compensation of ECs to maximize customer satisfaction under cost constraint. Finally, functional solutions of nursing bed are designed through the proposed QFD model, which are demonstrated to be effective and superior. The results indicate that the new proposed scenario -driven dual -layer network QFD model can capture latent RAs from nursing scenarios, take experts psychological preferences into consideration, provide a more precise ranking of ECs for the development of nursing bed functional solutions.
引用
收藏
页数:21
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