Real Time Controller for Laser Powder Bed Fusion Additive Manufacturing

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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.