A generative design technique for exploring shape variations

Shahroz Khan, Muhammad Junaid Awan

Research output: Contribution to journalArticle

9 Citations (Scopus)
4 Downloads (Pure)

Abstract

Because innovative and creative design is essential to a successful product, this work brings the benefits of generative design in the conceptual phase of the product development process so that designers/engineers can effectively explore and create ingenious designs and make better design decisions. We proposed a state-of-the-art generative design technique (GDT), called Space-filling-GDT (Sf-GDT), for the creation of innovative designs. The proposed Sf-GDT has the ability to create variant optimal design alternatives for a given computer-aided design (CAD) model. An effective GDT should generate design alternatives that cover the entire design space. Toward that end, the criterion of space-filling is utilized, which uniformly distribute designs in the design space thereby giving a designer a better understanding of possible design options. To avoid creating similar designs, a weighted-grid-search approach is developed and integrated into the Sf-GDT. One of the core contributions of this work lies in the ability of Sf-GDT to explore hybrid design spaces consisting of both continuous and discrete parameters either with or without geometric constraints. A parameter-free optimization technique, called Jaya algorithm, is integrated into the Sf-GDT to generate optimal designs. Three different design parameterization and space formulation strategies; explicit, interactive, and autonomous, are proposed to set up a promising search region(s) for optimization. Two user interfaces; a web-based and a Windows-based, are also developed to utilize Sf-GDT with the existing CAD software having parametric design abilities. Based on the experiments in this study, Sf-GDT can generate creative design alternatives for a given model and outperforms existing state-of-the-art techniques.
Original languageEnglish
Pages (from-to)712-724
Number of pages13
JournalAdvanced Engineering Informatics
Volume38
Early online date22 Oct 2018
DOIs
Publication statusPublished - 31 Oct 2018

Keywords

  • generative design
  • computer-aided design (CAD)
  • Jaya algorithm
  • parametric design
  • space-filling design

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