Niwa, Japan

Satoshi Eguchi

This inventor holds 1 USPTO granted patent. Top assignee: Okuma Machinery Works Ltd.. Active years: 1992.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Satoshi Eguchi. Retrieved from https://idiyas.com/inventor/satoshi-eguchi-jictvpgn

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0

Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 21(Granted Patents)


Company Filing History:


Years Active: 1992

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1 patent (USPTO):Explore Patents

Title: Satoshi Eguchi: Innovator in Machine Tool Technology

Introduction

Satoshi Eguchi is a notable inventor based in Niwa, Japan. He has made significant contributions to the field of machine tool technology, particularly in the area of abnormal state detection.

Latest Patents

Eguchi holds a patent for an "Abnormal State Detecting Apparatus of a Machine Tool." This innovative apparatus is designed to monitor a servomotor's performance by detecting abnormal acceleration and torque. The system identifies when both the torque and acceleration are outside normal parameters, indicating an abnormal operation state. When these conditions are met, the machine tool is deemed to be in an abnormal state, prompting the servomotor to be controlled to prevent damage.

Career Highlights

Satoshi Eguchi is associated with Okuma Machinery Works Ltd., a company renowned for its advanced machine tool solutions. His work has been instrumental in enhancing the reliability and safety of machine tools through innovative detection technologies.

Collaborations

Eguchi has collaborated with notable colleagues, including Takayoshi Kojima and Takayasu Asano, contributing to the advancement of machine tool technology.

Conclusion

Satoshi Eguchi's contributions to the field of machine tools, particularly through his patent on abnormal state detection, highlight his role as an innovator in this critical area of technology. His work continues to influence the safety and efficiency of machine operations.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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