Toronto, Canada

Taylor Mathewson

USPTO Granted Patents = 3 

Average Co-Inventor Count = 8.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023-2025

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3 patents (USPTO):Explore Patents

Title: **Innovations by Taylor Mathewson: Pioneering Machine Learning in Maintenance**

Introduction

Taylor Mathewson, an innovative inventor based in Toronto, Canada, has made significant strides in the field of industrial analytics. With a total of three patents to his name, he is recognized for his contributions to improving maintenance processes through the integration of machine learning technologies.

Latest Patents

One of Mathewson's most notable patents is focused on "Machine Learning Powered Anomaly Detection for Maintenance Work Orders." This revolutionary system applies statistical and machine learning analytics to both open and closed work orders, identifying potential problems and abnormalities that could adversely affect manufacturing and maintenance operations. The analysis system utilizes algorithms to learn standard maintenance behaviors and flags any abnormal practices that diverge significantly from established procedures. By doing so, the system can pinpoint costly maintenance practices, predict potential asset failures, and provide enterprise-specific recommendations aimed at minimizing machine downtime and optimizing maintenance workflows.

Career Highlights

Throughout his career, Taylor has held pivotal roles in notable companies, including Fiix Inc. and Rockwell Automation Technologies Incorporated. His work in these prominent organizations has been instrumental in advancing the application of machine learning in maintenance and industrial operations.

Collaborations

In his professional journey, Mathewson has collaborated with skilled individuals such as Mohammad Esmalifalak and Akshay Iyengar. These partnerships have undoubtedly contributed to his successes and innovations in the field.

Conclusion

Taylor Mathewson's innovative approach and patent contributions are reshaping the landscape of maintenance work orders. His work stands as a testament to the power of machine learning in enhancing operational efficiency and reducing downtime in industrial settings. As he continues to explore new avenues and technologies, the impact of his inventions will surely resonate within the industry.

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