A Redesign Modules Automatically Selecting Approach For Product-Service System Based On The Big Data Of Online Reviews And Product Usage Data

Product-service system (PSS) is a well-known concept which could guide manufacturing enterprises in servitization, reduce energy consumption and the environmental impacts and offer personalized solutions for users. Redesign existing products/service to optimize user experience is a critical task for manufacturing enterprises to carry out PSS. Traditional PSS design methods involve a lot of manual works such as investigations and interviews, which is time consuming. The aim of this paper is to propose a redesign modules automatically selecting approach to accelerate design automation. The big data is collected in the form of online reviews or product usage data caught by sensors, based on which, user experience of existing product/service is measured by FMEA. The Risk Priority Number (RPN) is computed automatically based on online reviews and product usage data. A case study of a crawler crane PSS redesign is performed to illustrate the feasibility and effectiveness of the proposed method.