Peoria, IL, United States of America

Stephen Paul Lu

USPTO Granted Patents = 2 

Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 14(Granted Patents)


Company Filing History:


Years Active: 2017-2019

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2 patents (USPTO):Explore Patents

Title: Innovations of Stephen Paul Lu

Introduction

Stephen Paul Lu is an accomplished inventor based in Peoria, Illinois. He has made significant contributions to the field of mobile wear detection technology. With a total of two patents to his name, Lu's work focuses on enhancing the efficiency and accuracy of wear detection in machinery.

Latest Patents

Lu's latest patents include "Command-driven automatic and semi-automatic mobile wear detection" and "Methods and systems for determining part wear based on digital image of part." The first patent outlines systems and methods for command-driven mobile wear detection. This method involves transmitting a request from a mobile device to determine a wear metric associated with a part. The device receives data indicating where it should be positioned and captures visual data once in the correct location. The mobile device then processes this visual data to determine the wear metric. The second patent describes a method for determining part wear using a mobile device by capturing digital images of a wear part and assessing its degree of wear based on those images.

Career Highlights

Stephen Paul Lu is currently employed at Caterpillar Inc., a leading company in the manufacturing of construction and mining equipment. His innovative work in mobile wear detection has the potential to improve maintenance practices and reduce downtime for machinery.

Collaborations

Lu has collaborated with notable colleagues, including Michael D. Hasselbusch and Mark Steven Diekevers. Their combined expertise contributes to the advancement of technology in their field.

Conclusion

Stephen Paul Lu's contributions to mobile wear detection technology exemplify the impact of innovation in machinery maintenance. His patents reflect a commitment to improving operational efficiency and accuracy in the industry.

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