Real Time Controller for Laser Powder Bed Fusion Additive Manufacturing

我们的团队最近开发和验证了几种用于添加剂制造(3D打印)中的激光粉末床融合过程的监测和控制策略，使用了感官信息，即声发射以及用于温度测量的高温计和红外摄像机。该实时控制器的目的是显著提高可添加制造部件的重复性、可靠性和质量，特别是在航空航天、汽车和医疗设备行业。实时控制器使用人工智能工具，特别是机器学习和深度学习来进行在线缺陷检测和过程控制。无需对成品零件进行破坏性测试，即可实时识别缺陷。这对于提高所生产零件的质量和优化制造过程，包括成本效益，是至关重要的。该控制器将在加拿大开发，使金属添加剂制造技术在加拿大工业中得到更广泛的采用。实现这一愿景的下一步是展示这项技术作为当前工业添加剂制造机器(3D打印机)的附加组件的适用性。这项新技术是为了提高当前工业3D打印机的能力和在工业中采用AM技术，以及满足工业中对额外制造部件认证的日益增长的需求而需要的。

Our group has recently developed and validated several monitoring and control strategies for the Laser Powder Bed Fusion process in Additive Manufacturing (3D printing) using sensory information namely acoustic emission as well as pyrometer and IR camera for temperature measurement. The aim of this real-time controller is to significantly improve the repeatability, reliability and quality of the additively manufactured parts particularly in the aerospace, automotive, and medical device industries. The real-time controller uses artificial intelligence tools, specifically machine learning and deep learning for on-line defect detection and process control. Defects are identified in real-time without the need for destructive testing of a finished part. This is essential for enhancing the quality of the parts produced and optimizing the manufacturing process including cost effectiveness. The controller will be developed in Canada resulting in wider adoption of the metal additive manufacturing technologies in Canadian industry. The next step toward fulfilling this vision is to demonstrate the applicability of this technology as an add on to current industrial additive manufacturing machines (3D printers). This new technology is needed for increasing the capabilities of current industrial 3D printers and the adoption of AM technologies in industry, as well as meeting the increased demand for additively manufactured part certification in industry.