Laser powder bed fusion for AI assisted digital metal components

This paper proposes a novel method to impart intelligence to metal parts using additive manufacturing. A sensor-embedded metal bracket is prototyped via a metal powder bed fusion process to recognise partial screw loosening or total screw missing or identify the source of vibration with the assistance of artificial intelligence (AI). The digital metal bracket can recognise subtle changes in the screw fixation state with 90% accuracy and identify unknown sources of vibration with 84% accuracy. The von Mises stress distribution in the prototyped metal bracket is evaluated using a finite element analysis, which is learned by AI to match the real-time deformation analysis of the metal bracket in augmented reality. The proposed prototype can contribute to hyper-connectivity for developing next-generation metal-based mechanical components.

本文提出了一种利用增材制造（additive manufacturing）为金属零部件赋予智能的全新方法。本研究通过金属粉末床熔融（metal powder bed fusion）工艺制备了嵌入传感器的金属支架原型，可借助人工智能（AI）识别螺钉局部松动、整体缺失，并定位振动源。该数字化金属支架对螺钉紧固状态的细微变化识别准确率可达90%，对未知振动源的识别准确率达84%。研究采用有限元分析（finite element analysis）对该金属支架原型的冯·米塞斯应力（von Mises stress）分布进行评估，并通过人工智能学习该分布结果，以匹配增强现实（augmented reality）环境下金属支架的实时形变分析。本研究所提出的原型系统可为下一代金属基机械构件的超互联化发展提供助力。