EOS partners with ORNL for metal AM quality control

August 5, 2022

The CRADA collaborative research project agreement includes the use of an on-site EOS M 290 metal 3D printer (Courtesy EOS GmbH)
The CRADA collaborative research project agreement includes the use of an on-site EOS M 290 metal Additive Manufacturing machine (Courtesy EOS GmbH)

EOS GmbH, headquartered in Krailling, Germany, has entered into a Cooperative Research and Development Agreement (CRADA) with the US Department of Energy for a collaborative research project at Oak Ridge National Laboratory (ORNL), Oak Ridge, Tennessee. The CRADA agreement includes an on-site EOS M 290 metal Additive Manufacturing and training for ORNL researchers on operation and data collection using EOSTATE MeltPool monitoring software.

Using on-axis sensors integrated into the beam path, EOSTATE measures the emissions of the melt pool, allowing insight into the Additive Manufacturing process. Various individually adjustable analysis parameters make it possible to evaluate the part quality, enabling users to improve R&D processes or optimise their production methods. Utilising this, ORNL intends to develop and test its own inspection techniques to identify new methodologies and approaches for quality assurance in Additive Manufacturing

“As Additive Manufacturing continues to generate greater levels of appeal for mass production, there is a growing requirement to ensure quality, and build upon one of the greatest strengths of 3D printing which is the capability to monitor parts as they are being built, layer-by-layer,” stated Dr Ankit Saharan, Senior Manager, Metals Technology at EOS. “If we can improve quality control processes to the point of making adjustments to builds in real-time, as anomalies are detected, that will save organisation’s time and energy while improving overall quality control.”

ORNL’s research will leverage several defect and anomaly detection processes to assess the accuracy of these methods in sample builds. ORNL has been working to develop a characterisation methodology using computed tomography (CT) to identify defects and anomalies in additively manufactured builds. To accomplish this, researchers will use two EOSTATE MeltPool Monitoring and EOSTATE Exposure OT (optical tomography) EOS methodologies.

Ryan Dehoff, ORNL’s Lead Researcher for Deposition Science and Technology, added, “If we can successfully demonstrate the ability to correlate in-situ data with metallurgical inspection, this could significantly change the paradigm of AM and enable mass production of AM components for a variety of high value industries.”

The CRADA will run for two years. A co-authored report outlining findings, including variables that have the most significant effect on the final part properties and an overall assessment of the variability in the process, is expected to be completed at the end of the engagement.



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