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A Survey on the Applications of Machine Learning in the Early Phases of Product Development

Part of: Knowledge-based Engineering

Published online by Cambridge University Press:  26 July 2019

Seyed Sina Shabestari ,
Michael Herzog  and
Beate Bender

Abstract

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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 phasesMachine learningSystem designRequirementsDesign knowledge
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 2437 - 2446
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

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