Abstract: Under the background of deep integration of manufacturing and service industries,an importance degree determination approach for Product Service System (PSS) modules based on user experience was proposed to support module redesign.Aiming at the hesitation of linguistic terms and the different preferences of each linguistic term in the process of expert evaluation,Probabilistic Linguistic Term set (PLTs) was used to evaluate the importance degrees of Customer Requirements (CRs) and relationships between CRs and modules,and the modules' importance degrees oriented to CRs was determined based on Quality Function Deployment (QFD).The experience dimensions were determined by factor analysis and the importance degrees of experience dimensions were evaluated by fuzzy set.The relationships between experience dimensions and modules were determined by PLTs.The modules' importance degrees oriented to experience were determined by importance degrees of experience dimensions and the relationship between experience dimensions and modules.An enterprise's improved intelligent robot PSS case study was carried out to illustrate the effectiveness of the proposed method.

Key words: product service system, user experience, quality function deployment, probabilistic linguistic term set, logistics robot

摘要： 针对制造业和服务业深度融合下的产品服务系统方案设计日益关注用户体验的问题,提出考虑用户体验的产品服务系统模块重要度判定方法以支持模块的再设计。针对专家评价过程中语言术语的犹豫性和每个语言术语偏好程度的不同,采用概率语言术语集评价用户需求重要度和用户需求与模块的关联关系,基于质量功能展开确定面向需求的模块重要度;采用因子分析确定体验维度,根据粗糙集确定体验维度重要度,采用概率语言术语集评价体验维度与模块的关联关系,确定面向体验的模块重要度;最后根据面向需求的重要度和面向体验的模块重要度确定模块重要度,并以某企业改进智能机器人产品服务系统模块重要度研究分析为例,验证了所提方法的有效性。

关键词: 产品服务系统, 用户体验, 质量功能展开, 概率语言术语集, 物流机器人