SBIR-STTR Award

Digital Twin Modeling of CNC Wiring Failures
Award last edited on: 9/20/2022

Sponsored Program
STTR
Awarding Agency
DOD : AF
Total Award Amount
$896,780
Award Phase
2
Solicitation Topic Code
AFX20D-TCSO1
Principal Investigator
Gerardo Mendoza

Company Information

United Aircraft Technologies Inc

Attn: UAt 30 3rd Street
Troy, NY 12180
   (469) 964-1992
   N/A
   www.uairtek.com

Research Institution

Ohio State University

Phase I

Contract Number: FA8649-21-P-0157
Start Date: 11/23/2020    Completed: 5/23/2021
Phase I year
2021
Phase I Amount
$150,000
United Aircraft Technologies (UAT) and Beacon Works are teaming up to provide a solution and tool for the scattered maintenance data and procedures. Electrical systems are great diagnostic and performance tools since it is what gives power to the entire platform. UAT has created a network of sensors that are embedded into clamps for wiring harnesses that can monitor, assess, diagnose, and collect data of the electrical system performance. Using modules and scattered data approach, UAT can use real-time and historical data to train algorithms to predict maintenance before a failure occurs. The data collected can also be used as a source of information to confirm ground truths, environmental data, and component performance. Real-time data dissemination requires the creation of dictionaries. Beacon has classified its dictionary to allow predictive maintenance to be trained on the classification and historical aircraft effect. Beacon can execute predictive maintenance via single records to maintenance organizations from planners to mechanics. Instead of trading condition of components for the historical records and replacement, Beacon combines both to execute an AI real-time holistic picture of the aircraft in need of service. This holistic picture has been found to increase the efficiency per flight hour.

Phase II

Contract Number: FA864922P0578
Start Date: 11/17/2021    Completed: 2/17/2023
Phase II year
2022
Phase II Amount
$746,780
UAT drives the advancement of smart manufacturing and the industrial IoT by integrating an electrical Health & Usage Monitoring System (eHUMS) and advanced data analytics using artificial intelligence (AI), machine-learning (ML), and operational intellige...