Enhancing Additive Manufacturing with Thermal Imaging and Machine Learning

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Scientists at the US Department of Energy’s Argonne National Laboratory have discovered a new method that uses thermal imaging and machine learning to improve additive manufacturing processes and detect structural defects in the metal parts they produce. Additive manufacturing, or 3D printing, is a process used by the construction industry for over a decade to create complex parts quickly and with a variety of materials. Unfortunately, the presence of structural defects during the building process has prevented additive manufacturing from being widely adopted.

Argonne’s new method uses X-ray technology to detect the formation of pores within the metal parts being created. These X-ray images are compared to thermal images generated by the additive manufacturing machine, allowing scientists to identify specific thermal signatures that indicate pore generation. A machine learning model is then trained with the data from these images to detect pores in other samples. When examined, the model produced near-perfect predictions of pore formation in real time.

This method can be implemented into existing commercial additive manufacturing systems without having to build new machines, making it a more practical solution. It also saves users time, money and materials by either adjusting parameters or stopping the build as soon as a major defect is detected, as well as providing a log file that helps inspectors find defects quickly and accurately. Going forward, the researchers hope to develop a comprehensive system with a variety of sensors that not only detects defective material but repairs it in the additive manufacturing process.

Argonne National Laboratory, founded in 1946, is the nation’s largest basic research laboratory and a major part of the US Department of Energy’s national laboratory system. Through scientific breakthroughs, the lab strives to address safety, economic and environmental issues. Its mission is to create a scientific and technological understanding to respond to global challenges and build an energy-secure future. Dr. Robert J. Rosner is the current Director of the laboratory.

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