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Additive Manufacturing at UTC
initial part material feedstock to final characterisation. The goal is to assimilate unstructured and pre-aggregated data into a database environment that facilitates trend generation and reporting. It is also using machine learning methods to
development and deployment. With more than ninety years of manufacturing experience and over 430 unique patent families in AM technologies, the company is uniquely qualified to integrate AM technology into the design process. Its combination of
“Its combination of physics-based models and in-process monitoring is unlocking an in-depth understanding of the process’s capabilities and limitations, which will advance adoption through the certification of material and machine combinations” enhance the build quality of additively manufactured parts and develop a deeper understanding of the AM process. Furthermore, the team is currently looking at the development of ‘smart’ parts, developed by embedding sensors in additively manufactured components. While industry peers are also pursuing Additive Manufacturing solutions, UTC believes that it is carving its own approach to accelerating AM
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physics-based models and in-process monitoring is unlocking an in-depth understanding of the process’s capabilities and limitations, which will advance adoption through the certification of material and machine combinations. In short, this heat exchanger project demonstrates how UTC’s holistic approach to AM balances the drive to get AM parts to production quickly, while achieving or exceeding aerospace quality standards.
Metal Additive Manufacturing | Summer 2019
Authors Venkat Vedula Executive Director, Additive Manufacturing Center of Expertise, United Technologies Corporation Vijay Jagdale Principal Engineer, Additive Manufacturing Center of Expertise United Technologies Corporation www.utc.com
References / notes [1] This material is based on research sponsored by Air Force Research Laboratory under agreement number FA8650-16-2-7230. The U.S. Government is authorised to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon.
The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory or the U.S. Government.
© 2019 Inovar Communications Ltd
Vol. 5 No. 2