Company Filing History:
Years Active: 2025
Title: Yotam Raz: Innovator in Additive Manufacturing Inspection
Introduction
Yotam Raz is a prominent inventor based in Tel Aviv, Israel. He has made significant contributions to the field of additive manufacturing, particularly in the area of product inspection. His innovative approach combines machine learning with traditional inspection methods to enhance the quality assurance processes in manufacturing.
Latest Patents
Yotam Raz holds a patent for a method of inspecting a product made by additive manufacturing. The patent, titled "Methods of inspecting a product made by additive manufacturing," outlines a process that utilizes an augmented file derived from a design file. This augmented file includes layer data used to produce the product and incorporates weighted layer data for design layers beneath each design layer. A machine learning algorithm, trained on previous images and augmented files, is applied to optical inspection images of the product during the additive manufacturing process to detect production errors. This innovative method aims to improve the reliability and accuracy of products created through additive manufacturing.
Career Highlights
Yotam Raz is currently employed at Nano Dimension Technologies, Ltd., a company known for its advancements in 3D printing and additive manufacturing technologies. His work at Nano Dimension has positioned him as a key player in the development of cutting-edge inspection methods that leverage technology to enhance manufacturing processes.
Collaborations
Yotam collaborates with talented individuals such as Eri Rubin and Itay Mosafi. Together, they contribute to the innovative environment at Nano Dimension Technologies, driving forward the company's mission to revolutionize the manufacturing landscape.
Conclusion
Yotam Raz's contributions to the field of additive manufacturing inspection exemplify the intersection of technology and innovation. His patent and work at Nano Dimension Technologies highlight the importance of integrating machine learning into manufacturing processes to ensure product quality.