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

Nordin, Axel LU (2017) In Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
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... (More)

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.

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author
organization
publishing date
type
Contribution to journal
publication status
epub
subject
keywords
Case Study, Design Automation, Engineering Design, Generative Design, Industrial Design
in
Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
pages
16 pages
publisher
Cambridge University Press
external identifiers
  • scopus:85011284365
ISSN
0890-0604
DOI
10.1017/S0890060416000536
language
English
LU publication?
yes
id
f14222bf-71c1-476f-a262-b14146278e89
date added to LUP
2017-02-14 13:25:22
date last changed
2018-01-07 11:49:38
@article{f14222bf-71c1-476f-a262-b14146278e89,
  abstract     = {<p>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.</p>},
  author       = {Nordin, Axel},
  issn         = {0890-0604},
  keyword      = {Case Study,Design Automation,Engineering Design,Generative Design,Industrial Design},
  language     = {eng},
  month        = {01},
  pages        = {16},
  publisher    = {Cambridge University Press},
  series       = {Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM},
  title        = {Challenges in the industrial implementation of generative design systems : An exploratory study},
  url          = {http://dx.doi.org/10.1017/S0890060416000536},
  year         = {2017},
}