Salem, MA, United States of America

Lauren Ashley Vahldick

This inventor holds 1 USPTO granted patent and 2 published patent applications and 1 EPO patent. Top assignee: General Electric Company. Active years: 2020.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Lauren Ashley Vahldick. Retrieved from https://idiyas.com/inventor/lauren-ashley-vahldick

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

USPTO Granted Patents = 1 

% Patents Active = 100.0

 

Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: Lauren Ashley Vahldick and Usage-Based Lifing

Introduction

Lauren Ashley Vahldick is an inventor associated with Salem, Massachusetts, and General Electric Company. Her patent work addresses predicting the use and fatigue of gas turbine engines on aerial vehicles.

Latest Patents

Vahldick is associated with 1 patent, titled “Usage Based Lifing.” The invention describes systems and methods for predicting usage-based lifing and low-cycle fatigue consumption. One example method uses historical flight data and information about an aerial vehicle’s operating conditions, determines whether a flight is usable for analysis, and applies machine learning to build a model correlating flight data with low-cycle fatigue consumption.

Career Highlights

Vahldick’s listed patent reflects work at the intersection of aviation, engine monitoring, and machine learning. By using operational and flight data to estimate fatigue consumption, the disclosed approach aims to support analysis of gas turbine engine usage.

Collaborations

The patent information also names Ronald Burton Wight and Simon Shu Kong Chan as coworkers associated with Vahldick’s work.

Conclusion

Lauren Ashley Vahldick’s patent highlights a data-driven approach to estimating gas turbine engine usage and low-cycle fatigue, connecting aviation operations with machine-learning-based analysis.

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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