论文标题
用于制造成本估算和加工功能可视化的可解释人工智能
Explainable Artificial Intelligence for Manufacturing Cost Estimation and Machining Feature Visualization
论文作者
论文摘要
近年来，基于深度学习的制造成本预测的研究已经开始，但是由于模型仍然用作黑匣子，因此无法解释成本预测的理由。这项研究旨在提出使用可解释的人工智能的3D计算机辅助设计（CAD）模型的制造成本预测过程。拟议的过程可以可视化3D CAD模型的加工功能，从而影响制造成本的增加。所提出的过程包括（1）数据收集和预处理，（2）3D深度学习体系结构探索以及（3）可视化以解释预测结果。提出的深度学习模型显示了计算机数值控制（CNC）机加工零件的制造成本的高可预测性。特别是，使用3D梯度加权类激活映射证明，所提出的模型不仅可以检测CNC加工功能，还可以区分同一功能的加工难度。使用拟议的过程，我们可以为工程设计师提供设计指导，以降低概念设计阶段的制造成本。我们还可以为在线制造平台客户提供实时报价和重新设计建议。
Studies on manufacturing cost prediction based on deep learning have begun in recent years, but the cost prediction rationale cannot be explained because the models are still used as a black box. This study aims to propose a manufacturing cost prediction process for 3D computer-aided design (CAD) models using explainable artificial intelligence. The proposed process can visualize the machining features of the 3D CAD model that are influencing the increase in manufacturing costs. The proposed process consists of (1) data collection and pre-processing, (2) 3D deep learning architecture exploration, and (3) visualization to explain the prediction results. The proposed deep learning model shows high predictability of manufacturing cost for the computer numerical control (CNC) machined parts. In particular, using 3D gradient-weighted class activation mapping proves that the proposed model not only can detect the CNC machining features but also can differentiate the machining difficulty for the same feature. Using the proposed process, we can provide a design guidance to engineering designers in reducing manufacturing costs during the conceptual design phase. We can also provide real-time quotations and redesign proposals to online manufacturing platform customers.
