Abstract Rapid advancements in artificial intelligence and immersive technologies are revolutionizing various sectors, notably product design. However, the traditional personalized design process, which depends on predefined elements with limited user input, often results in products that do not fully align with individual preferences and lack substantial user engagement. To fill this gap, the emergence of AI-generated content (AIGC) presents a significant opportunity for mass personalization through natural language interactions. Inspired by this paradigm, this paper proposes an AIGC-enabled personalized product design approach, which integrates a configuration retrieval model with a fine-tuned text-to-3D generative model (TAPS3D model), thereby enabling users to create personalized products within an immersive environment. While the current system requires approximately two minutes for 3D shape generation, this level of responsiveness is considered suitable for concept exploration in early-stage design workflows, where rapid iteration is prioritized over instantaneous feedback. Furthermore, a case study is conducted on the design of personalized steering wheels, to demonstrate the feasibility of this methodology. The effectiveness of the proposed approach in improving user experience is evaluated through a comparative experiment against the traditional configuration system. The findings indicate that our proposed AIGC-enabled personalized design system effectively enhances personalization, facilitates user engagement, improves the interaction experience, and increases user satisfaction.
Ren et al. (Thu,) studied this question.
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