PREDICTRONICS RECEIVES PHASE II SMALL BUSINESS INNOVATION RESEARCH AWARD
AUGUST 13, 2020
Predictronics is proud to announce we have received a second phase Small Business Innovation Research award.
In January 2020, Predictronics received a phase one SBIR grant under the U.S. Navy Technology Acceleration program to develop machine learning (ML) and artificial intelligence (AI) capabilities to impact mission success (Navy SBIR 2019.3 - Topic N193-A01). This program supports the progress of these innovative technologies to address a variety of naval applications and challenges.
After achieving successful results in phase one validating our analytics methodology against three public data sets, our team was able to create a demonstration-ready software prototype for identifying, labelling, diagnosing and predicting failures in critical aircraft systems.
The goal of phase two is to further validate our solution using additional relevant datasets provided by partners in the aerospace industry. With these datasets, Predictronics will also expand the solution capabilities, providing labels for anomalous patterns from maintenance and inspection records, as well as optimizing the settings and parameters used in our analysis methodology. Another key goal of this phase will be the further automation of fault identification and labelling, which will reduce the need for human effort.
Our solution will have the ability to identify and predict faults with a high degree of precision, which will positively impact naval aircraft systems, resulting in quicker and more accurate diagnosis, lower maintenance costs, higher fleet availability, and greater operational efficiency. The functionality of this solution can also be applied to a wide range of industries beyond military and commercial aircraft, including manufacturing, ground transportation, energy, and more.
To learn more about our work from phase one of this SBIR project, view our use case here.
To read about our successful work in the aerospace industry, check out our use case on predictive maintenance for commercial aircraft here.
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