With the rapid development of artificial intelligence in recent years, the use of generative design to assist in design decision-making has become an important topic. Bamboo, as a low-carbon and resilient material, is widely applied in architecture and furniture manufacturing. This study explores iterative generative design based on the bending properties of bamboo, combining performance analysis software to optimize the structure and plan the manufacturing process. The entire workflow from design to manufacturing is completed. The results demonstrate that the integration of artificial intelligence with performance-based analysis enables the seamless combination of computational innovation in design and practical construction, facilitating AI’s full involvement in the entire process from design to construction. This approach provides new insights into the innovation of generative design for bamboo materials.

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Performance-Driven Structure in AIGC: An AI-Driven Workflow of Bamboo Chair Design and Fabrication

  • Shitong Wang,
  • Yulu Zhang,
  • Yige Liu,
  • Philip F. Yuan

摘要

With the rapid development of artificial intelligence in recent years, the use of generative design to assist in design decision-making has become an important topic. Bamboo, as a low-carbon and resilient material, is widely applied in architecture and furniture manufacturing. This study explores iterative generative design based on the bending properties of bamboo, combining performance analysis software to optimize the structure and plan the manufacturing process. The entire workflow from design to manufacturing is completed. The results demonstrate that the integration of artificial intelligence with performance-based analysis enables the seamless combination of computational innovation in design and practical construction, facilitating AI’s full involvement in the entire process from design to construction. This approach provides new insights into the innovation of generative design for bamboo materials.