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EOS and US DOE to conduct metal AM quality control research at ORNL

The Oak Ridge National Laboratory will use AM technology to conduct quality control research around in-situ monitoring

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EOS, a leading supplier for responsible manufacturing solutions based on industrial 3D printing technology, has entered into a Cooperative Research and Development Agreement (CRADA) with the US Department of Energy (DOE) for a collaborative research project, concerning AM quality control, at Oak Ridge National Laboratory (ORNL). The CRADA agreement includes an on-site EOS M 290 metal 3D printer and training for ORNL researchers on the operation and data collection using EOSTATE MeltPool monitoring software.

EOS and US Department of Energy (DOE) to conduct metal AM quality control research in-situ monitoring at Oak Ridge National Laboratory
EOS M 290

Using on-axis sensors integrated into the beam path, EOSTATE measures the emissions of the melt pool – giving deeper insight into the 3D printing process. Various individually adjustable analysis parameters make it possible to evaluate the part quality. The features of EOSTATE MeltPool make it well-suited to users who want to improve their research and development processes, or optimize their production methods. In addition to this, ORNL is developing and testing 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,” said Dr. Ankit Saharan, senior manager in the metals technology division 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 organizations time and energy while improving overall quality control.”

ORNL’s quality control 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 characterization methodology using computed tomography (CT) to identify defects and anomalies in 3D printed builds. To accomplish this, researchers will use two EOSTATE MeltPool Monitoring and EOSTATE Exposure OT (optical tomography) EOS methodologies.

“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,” said Ryan Dehoff, ORNL’s lead researcher for deposition science and technology.

The CRADA will run for a period of 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, will be completed at the end of the engagement.

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Edward Wakefield

Edward is a freelance writer and additive manufacturing enthusiast looking to make AM more accessible and understandable.

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