Application of human-machine collaborative creative generation process in industrial design

This paper proposes a closed-loop human-machine co-creation process suitable for the early stages of industrial design. By integrating the Stable Diffusion model with the LoRA fine-tuning strategy, and constructing an image quality evaluation mechanism based on the dual metrics of CLIP and CMMD, the system guides designers in filtering and providing feedback on generated outputs to iteratively optimize prompts. The system integrates automatic scoring, manual filtering, and keyword clustering recommendation to form a collaborative closed loop of generationselectionoptimization. In a desk lamp design task, experiments demonstrate that this process significantly enhances the consistency of image styles and the quality of creative expression. The study verifies the feasibility of the human-machine collaboration mechanism in complex design tasks and offers a new paradigm for the application of generative AI in industrial product design.