Beyond Rendering Generation: A Production-Aware AI Co-creation System for Suzhou Ming-Style Furniture Cultural Heritage

Abstract

As a representative of cultural heritage, Suzhou Ming-style furniture embodies a composite knowledge system integrating material properties, structure, and craftsmanship. While Generative AI shows potential in creative design, current models lack an intrinsic understanding of physical and manufacturing constraints, often producing unproducible visual illusions. To bridge the gap between pixelated images and actual production, this paper proposes and develops a production-aware AI co-creation system that translates implicit traditional craftsmanship into explicit digital rules. Utilizing a node-based workflow and a knowledge-embedded estimation module, the system connects creative exploration with production configuration. It generates multimodal outputs, including renderings, structural exploded views, and practical cost and timeline estimations. Preliminary evaluations indicate high consistency with actual workshop production experience, effectively lowering the creative threshold for non-professionals. This research demonstrates how AI transcends mere visual generation to become a new pathway for the dynamic preservation and revitalization of cultural heritage.