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AI image generation application for Kansei engineering design process - milk carton case
  • Shigekazu Ishihara ,
  • Rueikai Kuo ,
  • Keiko Ishihara
Shigekazu Ishihara
Hiroshima International University

Corresponding Author:[email protected]

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Rueikai Kuo
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Keiko Ishihara
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Abstract

This study shows the application of AI image generators with fine-tuning to the Kansei engineering design process.  Kansei engineering is a method for surveying and analyzing users’ latent feelings and preferences to product and service development (Nagamachi, 1991, 2011).. There are several common difficulties in applying Kansei engineering, including a lack of variety in evaluation samples, the need for non-designers to participate in the design process, and the fact that designers are often too busy to fully engage in the design process. In order to address these challenges, we have applied an AI image generator, StableDiffusion  (Rombach et al. 2021),to the Kansei engineering design process. The “Hypernetworks” framework to fine-tune StableDiffusion in order to make better representation of the shape and appearance of milk cartons. Based on previous Kansei engineering study on milk cartons (Ishihara et al., 1996) , several attempts are shown to use AI-generated designs to create innovative and visually appealing milk carton designs, including designs incorporating red and blue colors and abstract shapes, and a design inspired by the abstract paintings of Jackson Pollock. The authors conclude that the use of AI technology can be a valuable tool in boosting innovative design through Kansei engineering, and that further research is needed to explore the potential for interaction between humans and AI in the design process.