Product design and evaluation methods based on AI-generated content
Generative artificial intelligence(GAI)has become a transformative force in product design,significantly enhancing design efficiency.However,systematic application methods and cases of collaborative multi-type GAI application examples remain scarce.To highlight the innovative role of GAI in product design,a method based on AI-generated content(AIGC)for product form design and evaluation was proposed.First,ChatGPT was utilized to capture the emotional needs of target product users and summarize them into design target imageries.Additionally,ChatGPT served as a prompt generator for Midjourney,generating necessary prompt phrases for the target product.Midjourney constructed a reference library for product forms using these target imageries and prompt phrases.Perceptual questionnaires were then utilized to select distinctive designs as alternatives.Next,the grey relational analysis(GRA)and analytic hierarchy process(AHP)methods were employed to evaluate these alternatives and select the optimal design,with Rhino used to optimize human-machine interaction.Finally,stable diffusion was utilized to quickly generate rendering effects for the optimal design.A case study on electric motorcycles and household vacuum cleaners validated the proposed method.It was found that the collaborative model of multi-type generative AI excelled in analyzing user needs,transforming design concepts,and optimizing design details.This approach revolutionized traditional design processes and improved design efficiency.The proposed method provided product designers with an AIGC-based design approach and established a quantitative evaluation method for AIGC.
form designgenerative AIdesign evaluationgrey relationship analysisanalytic hierarchy process
万方数据
维普
