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Challenges in the industrial implementation of generative design systems: An exploratory study

Published online by Cambridge University Press:  30 January 2017

Axel Nordin*
Affiliation:
Division of Product Development, Department of Design Sciences, Faculty of Engineering LTH, Lund University, Lund, Sweden
*
Reprint requests to: Axel Nordin, Division of Product Development, Department of Design Sciences, Faculty of Engineering LTH, Lund University, P.O. Box 118, Lund 221 00, Sweden. E-mail: axel.nordin@design.lth.se

Abstract

The aim of this paper is to investigate the challenges associated with the industrial implementation of generative design systems. Though many studies have been aimed at validating either the technical feasibility or the usefulness of generative design systems, there is, however, a lack of research on the practical implementation and adaptation in industry. To that end, this paper presents two case studies conducted while developing design systems for industrial uses. The first case study focuses on an engineering design application and the other on an industrial design application. In both cases, the focus is on detail-oriented performance-driven generative design systems based on currently available computer-assisted design tools. The development time and communications with the companies were analyzed to identify challenges in the two projects. Overall, the results show that the challenges are not related to whether the design tools are intended for artistic or technical problems, but rather in how to make the design process systematic. The challenges include aspects such as how to fully utilize the potential of generative design tools in a traditional product development process, how to enable designers not familiar with programming to provide design generation logic, and what should be automated and what is better left as a manual task. The paper suggests several strategies for dealing with the identified challenges.

Type
Regular Articles
Copyright
Copyright © Cambridge University Press 2017 

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