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English(EN) CAD-feature enhanced machine learning for manufacturing effort estimation on sheet metal bending parts

CAD增强型机器学习改进钣金件弯曲工作量估算

研究人员开发了一种新颖的机器学习方法,用于估算钣金件弯曲的制造工作量。该方法通过将弯曲特性和表面角色等特定于制造的特征集成到CAD模型的几何表示中,来增强基于图的学习。通过将领域知识与数据驱动的见解相结合,该方法旨在提高工业CAD环境中可制造性预测和工作量估算的准确性。 AI

影响 这种混合方法有望提高工业CAD系统中可制造性评估和工作量估算的准确性。

排序理由 该集群包含一篇详细介绍新机器学习方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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CAD增强型机器学习改进钣金件弯曲工作量估算

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Joost R. Duflou ·

    CAD-feature enhanced machine learning for manufacturing effort estimation on sheet metal bending parts

    Graph-based machine learning has emerged as a promising approach for manufacturability analysis by learning directly from CAD models represented as Boundary Representations (B-reps), exploiting both surface geometry and topological connectivity. However, purely geometric represen…