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<p>The accelerating digitalization of the construction sector has brought into sharp focus the inefficiencies and labor-intensive nature inherent in traditional craftsmanship for historical architecture. In response, this study proposes an AI-driven generative design workflow that translates semantic inputs into 2D imagery and 3D models, enabling the systematic learning and replication of stylistic features from a quintessential southern Chinese architectural ornament—the Lingnan stucco relief. This approach moves beyond the conventional reliance on individual expertise and heuristic empirical methods. The structural performance of the AI-generated designs was evaluated through combined material testing and numerical simulations. Concurrently, hybrid additive manufacturing techniques were explored for rapid physical prototyping. Collectively, this integrated framework illustrates the feasibility of revitalizing traditional craft practices within a contemporary intelligent paradigm, offering a technological pathway for the preservation and renovation of historic built heritage.</p>

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Coupling generative AI with 3D printing for historical building renovation: a case study of Lingnan stucco relief

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月3日

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  • Yiwei Yin,
  • Jiale Cheng,
  • Jiashao Zhou,
  • Zhengyanglin Xiao,
  • Wenhao Chen,
  • Hao Zheng,
  • Nan Hu

摘要

The accelerating digitalization of the construction sector has brought into sharp focus the inefficiencies and labor-intensive nature inherent in traditional craftsmanship for historical architecture. In response, this study proposes an AI-driven generative design workflow that translates semantic inputs into 2D imagery and 3D models, enabling the systematic learning and replication of stylistic features from a quintessential southern Chinese architectural ornament—the Lingnan stucco relief. This approach moves beyond the conventional reliance on individual expertise and heuristic empirical methods. The structural performance of the AI-generated designs was evaluated through combined material testing and numerical simulations. Concurrently, hybrid additive manufacturing techniques were explored for rapid physical prototyping. Collectively, this integrated framework illustrates the feasibility of revitalizing traditional craft practices within a contemporary intelligent paradigm, offering a technological pathway for the preservation and renovation of historic built heritage.