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A personalized requirement identifying model for design improvement based on user profiling

Published online by Cambridge University Press:  27 November 2019

Jing Li*
Affiliation:
Institute of Design Management, Northwestern Polytechnical University, Xi'an, China
Xinwei Zhang
Affiliation:
Institute of Design Management, Northwestern Polytechnical University, Xi'an, China
Keqin Wang
Affiliation:
Institute of Design Management, Northwestern Polytechnical University, Xi'an, China
Chen Zheng
Affiliation:
Mechanical Engineering School, Northwestern Polytechnical University, Xi'an, China
Shurong Tong
Affiliation:
Institute of Design Management, Northwestern Polytechnical University, Xi'an, China
Benoit Eynard
Affiliation:
Department of Mechanical Systems Engineering – UMR 7337 Roberval, Sorbonne Universités, Université de Technologie de Compiègne, Compiègne Cedex, France
*
Author for correspondence: Jing Li, E-mail: lijing2015@nwpu.edu.cn

Abstract

The personalization of products and services has become an inevitable trend in the manufacturing and service industry, but it is very difficult to identify users' personalized requirements accurately. This paper solves this problem by constructing an identifying model for personalized requirement based on user profiling. Firstly, the framework of the proposed model and the process of identifying the user's personalized requirements with this model are introduced, and then an experimental scheme for obtaining users' profiling data is designed. On this basis, an experiment is performed by investigating users' requirements for the computer to obtain the data, and the data are used for the analysis based on the proposed model. The analysis result shows that the model can reveal the difference among heterogeneous users well, find out the implicit requirements of users, and identify the gap between existing products and users' personalized requirements, which provides support to the subsequent improvement of product design.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2019

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