A survey on the applications of machine learning in the early phases of product development

DS 94: Proceedings of the Design Society: 22nd International Conference on Engineering Design (ICED19)

Year: 2019
Editor: Wartzack, Sandro; Schleich, Benjamin; Gon
Author: Shabestari, Seyed Sina; Herzog, Michael; Bender, Beate
Series: ICED
Institution: Ruhr Universit
Section: Knowledge-based engineering
DOI number: https://doi.org/10.1017/dsi.2019.250
ISSN: 2220-4342


Machine learning has shown its potential to support the knowledge extraction within the development processes and particularly in the early phases where critical decisions have to be made. However, the current state of the research in the applications of the machine learning in the product development are fragmented. A holistic overall view provides the opportunity to analyze the current state of research and is the basis for the strategic planning of future research and the actions needed. Hence, implementing the systematic literature survey techniques, the state of the applications of machine learning in the early phases of the product development process namely the Requirements, functional modelling and principal concept design is reviewed and discussed.

Keywords: Early design phases, Machine learning, System design, Requirements, Design knowledge


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