Barberton, OH, United States of America

Ryan Steven Wackerly


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Ryan Steven Wackerly: Innovator in Weld Inspection Technology

Introduction

Ryan Steven Wackerly is an accomplished inventor based in Barberton, OH (US). He has made significant contributions to the field of welding technology through his innovative patent. His work focuses on enhancing the quality inspection processes in welding, which is crucial for various industrial applications.

Latest Patents

Wackerly holds a patent for an "In-situ inspection method based on digital data model of weld." This method inspects weld quality in real-time by obtaining a plurality of sequenced images of an in-progress welding process. It generates a multi-dimensional data input based on these images and various weld process control parameters. These parameters include shield gas flow rate, temperature, pressure, voltage, amperage, wire feed rate, and part preheat/inter-pass temperature. The method utilizes computer vision techniques to generate defect probability and analytics information, providing predictive insights on the quality features of the welding process. Ultimately, it creates a 3-D visualization of the as-welded regions for virtual inspection and quality determination.

Career Highlights

Wackerly is currently employed at Bwxt Advanced Technologies LLC, where he applies his expertise in welding technology. His innovative approach has positioned him as a key player in the development of advanced inspection methods.

Collaborations

Wackerly collaborates with talented individuals such as Ryan Scott Kitchen and Matthew Paul Levasseur, contributing to a dynamic work environment that fosters innovation and creativity.

Conclusion

Ryan Steven Wackerly's contributions to welding inspection technology exemplify the impact of innovation in industrial processes. His patent not only enhances the quality assurance of welding but also showcases the importance of real-time data analysis in manufacturing.

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