Albuquerque, NM, United States of America

Kevin C Anderson

USPTO Granted Patents = 1 

Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2022

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1 patent (USPTO):Explore Patents

Title: Kevin C Anderson: Innovator in Additive Manufacturing

Introduction

Kevin C Anderson is a notable inventor based in Albuquerque, NM (US). He has made significant contributions to the field of additive manufacturing, particularly through his innovative use of machine learning to identify defects in manufacturing processes. His work is instrumental in enhancing the efficiency and reliability of additive manufacturing systems.

Latest Patents

Kevin holds a patent titled "Defect identification using machine learning in an additive manufacturing system." This patent describes an advanced additive manufacturing system that includes an apparatus for distributing layers of metallic powder across a build plane. The system utilizes a power source to emit a beam of energy that fuses the metallic powder into parts. A processor within the system steers the energy beam and collects data from sensors that detect electromagnetic energy emitted during the fusion process. This data is then converted into parameters that indicate conditions at the build plane, which are used as inputs for a machine learning algorithm to detect defects in the fused metallic powder.

Career Highlights

Kevin is currently employed at Sigma Labs, Inc., where he continues to develop innovative solutions in the field of additive manufacturing. His expertise in integrating machine learning with manufacturing processes sets him apart as a leader in this rapidly evolving industry.

Collaborations

Some of Kevin's coworkers include Darren Beckett and Roger Frye, who contribute to the collaborative environment at Sigma Labs, Inc. Their combined efforts enhance the company's ability to push the boundaries of additive manufacturing technology.

Conclusion

Kevin C Anderson's work in additive manufacturing and machine learning exemplifies the innovative spirit of modern engineering. His contributions are paving the way for more efficient and reliable manufacturing processes, showcasing the potential of technology in transforming industries.

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