McKay, A. orcid.org/0000-0002-8187-4759, Hazlehurst, T.A., de Pennington, A. et al. (1 more author) (2023) Design descriptions in the development of machine learning based design tools. In: Proceedings of the Design Society. International Conference on Engineering Design, ICED23, 24-28 Jul 2023, Bordeaux, France. Cambridge University Press , pp. 1227-1236.
Abstract
Applications of machine learning technologies are becoming ubiquitous in many sectors and their impacts, both positive and negative, are widely reported. As a result, there is substantial interest from the engineering community to integrate machine learning technologies into design workflows with a view to improving the performance of the product development process. In essence, machine learning technologies are thought to have the potential to underpin future generations of data-enabled engineering design system that will deliver radical improvements to product development and so organisational performance. In this paper we report learning from experiments where we applied machine learning to two shape-based design challenges: in a given collection of designed shapes, clustering (i) visually similar shapes and (ii) shapes that are likely to be manufactured using the same primary process. Both challenges were identified with our industry partners and are embodied in a design case study. We report early results and conclude with issues for design descriptions that need to be addressed if the full potential of machine learning is to be realised in engineering design.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | Ⓒ The Author(s), 2023. Published by Cambridge University Press. 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. |
Keywords: | Big data; Artificial intelligence; Design informatics |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Aug 2023 09:36 |
Last Modified: | 11 Aug 2023 09:36 |
Status: | Published |
Publisher: | Cambridge University Press |
Identification Number: | 10.1017/pds.2023.123 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202191 |
Download
Filename: design-descriptions-in-the-development-of-machine-learning-based-design-tools.pdf
Licence: CC-BY-NC-ND 4.0