Towards product evolution: from the perspective of user knowledge

Abstract

In the field of engineering design, design for evolution is an economic and effective tactic to deal with changing customer requirements, in which the quantification of the product evolution degree between adjacent product generations is vital. Under the knowledge economy environment, user knowledge includes personalised experience, which can be used to develop competitive and creative products. The evolution of user knowledge can be applied to monitor product evolution to a certain extent. Thus, an evolution model is established to quantify the product evolution degree by integrating a user knowledge network, the Girven–Newman algorithm, latent Dirichlet allocation, an information axiom, and an evolution map. These methods are adopted to determine the knowledge topics for each product generation and to quantify the evolution degree of the current product generation, while the inheritance relation between each pair of knowledge clusters in two adjacent product generations is considered. Finally, the evolution process modelling of iPhone is performed as a case study to evaluate the effectiveness of the proposed method. The results show that the evolution map and curve to visualise the evolution process, and the evolution patterns and mechanisms are deduced to assist designers in forecasting future trends.

KEYWORDS:

• Product evolution
• user knowledge network
• Girven–Newman algorithm
• latent Dirichlet allocation
• information axiom
• evolution map

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, [Zhang Mengting], upon reasonable request.

Additional information

Funding

This project was supported by National Natural Science Foundation of China: [No. 51505480, 72001203].

Notes on contributors

Yupeng Li

Yupeng Li is an Associate Professor in the school of mines at China University of Mining and Technology. His research interests lie at data mining and pattern recognition, product and service engineering and engineering decision theory.

Mengting Zhang

Mengting Zhang is now a PhD student in the school of Economics and Management at China University of Mining and Technology. She focuses on the product evolution and data mining.

Na Zhang

Na Zhang is a lecturer in the school of mines at China University of Mining and Technology. Her focus is on Product collaborative design, product design change management and logistics engineering.

Hongyan Jiang

Hongyan Jiang is a professor in the school of mines at the China University of Mining and Technology. Her focus is on Brand management, Consumer behaviour and management psychology.