Gregory David Adams

Title: Gregory David Adams: Innovator in Predictive Maintenance Technology

Introduction

Gregory David Adams is a notable inventor based in Oklahoma City, OK (US). He has made significant contributions to the field of predictive maintenance technology, particularly in the area of reciprocating compressors. His innovative approach has the potential to enhance machine reliability and operational efficiency.

Latest Patents

Adams holds a patent for a "Method of predicting failure events for reciprocating compressors." This patent describes a system and process that begins with loading a slope signature library into the control system. The library correlates time-to-failure based on rates of change of one or more measured conditions. The process involves activating the machine, determining baseline measurements, and detecting any out-of-spec measurements. Once an out-of-spec measurement is identified, the rate of change is determined, and a slope signature is calculated. This signature is then compared against the library to predict the time-to-failure, allowing for modifications in machine operation to extend its lifespan. Adams has 1 patent to his name.

Career Highlights

Gregory David Adams is currently employed at GE Oil & Gas UK Limited, where he applies his expertise in predictive maintenance. His work focuses on improving the reliability of machinery, which is crucial in the oil and gas industry. His innovative methods have the potential to save companies significant costs associated with machine failures.

Collaborations

Adams has collaborated with notable colleagues such as Sheldon McCrackin and Sam Stroder. Their combined efforts contribute to advancements in technology and the development of effective predictive maintenance solutions.

Conclusion

Gregory David Adams is a pioneering inventor whose work in predictive maintenance technology is making waves in the industry. His patent for predicting failure events in reciprocating compressors showcases his innovative thinking and dedication to improving machine reliability. His contributions are valuable assets to the field and will likely influence future developments in predictive maintenance.