Diffusion model-driven smart design and manufacturing: Prospects and challenges

Artificial Intelligence-Generated Content (AIGC), particularly diffusion models as a key component of Generative Artificial Intelligence (GenAI), are transforming smart design and manufacturing in the interplay of Industry 4.0 and Industry 5.0. This paper analyzes the applications of diffusion models in smart design and manufacturing, focusing on three key pillars: diffusion-driven generative design, smart control, and fault diagnosis. Diffusion models enhance manufacturing system flexibility, resilience, and sustainability through their applications as generative design engines, intelligent controllers for adaptive manufacturing processes, and predictive tools for fault diagnosis. This study provides a comprehensive review of the current state of diffusion model-driven smart design and manufacturing. It analyzes key challenges such as model efficiency, data dependency, and system integration, while providing a constructive perspective on potential solutions. This paper also integrates Industry 5.0 considerations by connecting the applications and technical solutions to the core values of human-centricity, sustainability, and resilience. It concludes by emphasizing the necessity of continuous refinement of diffusion models and interdisciplinary research to integrate them into smart design and manufacturing systems further, fostering a more human-centric, resilient, and sustainable industry.