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

Research output: Contribution to journalArticle


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.


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Production Engineering, Human Work Science and Ergonomics


  • Case Study, Design Automation, Engineering Design, Generative Design, Industrial Design
Original languageEnglish
Pages (from-to)16-31
JournalArtificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Issue number01
Early online date2017 Jan 30
Publication statusPublished - 2018 Feb
Publication categoryResearch