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Guangdong Provincial Key Laboratory of Future Networks of Intelligence

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Representative Papers

AIMold: An Autonomous AI-based Pipeline for Complex Mold Design

Aug 01, 2026

This study addresses the longstanding reliance on expert knowledge in designing injection molds for complex plastic parts, a process hindered by the absence of automated methods and publicly available data. To bridge this gap, the authors introduce MoldCAD, the first large-scale structured CAD dataset dedicated to complex mold design, comprising 4,934 parts and 3,850 complete mold assemblies. They further propose an end-to-end AI pipeline that leverages deep learning to predict parting directions, generate parting surfaces, identify auxiliary components, and perform assembly reasoning—directly producing manufacturing-ready mold designs. The method successfully generates over 23,000 fabricable mold components, achieving, for the first time, fully automatic translation from part geometry to complete mold assembly and advancing the frontier of manufacturing-aware CAD generation.

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Latest Papers

AIMold: An Autonomous AI-based Pipeline for Complex Mold Design

Aug 01, 2026

This study addresses the longstanding reliance on expert knowledge in designing injection molds for complex plastic parts, a process hindered by the absence of automated methods and publicly available data. To bridge this gap, the authors introduce MoldCAD, the first large-scale structured CAD dataset dedicated to complex mold design, comprising 4,934 parts and 3,850 complete mold assemblies. They further propose an end-to-end AI pipeline that leverages deep learning to predict parting directions, generate parting surfaces, identify auxiliary components, and perform assembly reasoning—directly producing manufacturing-ready mold designs. The method successfully generates over 23,000 fabricable mold components, achieving, for the first time, fully automatic translation from part geometry to complete mold assembly and advancing the frontier of manufacturing-aware CAD generation.

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