The COVID-19 pandemic presented unique challenges this past year for Predictronics, our customers, the greater economy, and the world. Although we certainly felt the impact, we were fortunate to have the ability to continue delivering impact to our customers, both existing and new, through many successful and impactful engagements. We were also grateful to have been recognized on a number of occasions for our technology, innovation, and proven expertise in machine learning and AI-driven solutions for industrial applications.

At the end of 2019, Predictronics received a phase one Small Business Innovation Research award 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). After achieving successful results in phase one and validating our AI-based analytics methodology, our team was able to create a demonstration-ready prototype for identifying, labelling, diagnosing, and predicting failures in critical aircraft systems.

In June 2020, Predictronics was the recipient of a phase two SBIR award from the U.S. Navy.

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 is also currently working to 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 is to further the 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.

In August 2020, Predictronics was announced the winner of the AI Data Challenge for Intralogistics Centers organized by Siemens Digital Industries Customer Services (DI CS). The goal of this data challenge was to propose and validate a predictive maintenance approach that would detect and prevent the failure of Automatic Storage and Retrieval Machines (ASRM) in the warehouse and fulfillment industry. Our successful predictive solution was able to accurately predict ASRM failure 11 days before it occurred. As a result of winning this data challenge, Predictronics was granted the opportunity to continue our work with Siemens through a commercial engagement. The objective of this engagement has been to refine and further validate our winning solution through deployment at a Siemens facility.

Predictronics received two 2020 Innovation & Technology Awards from the Cincinnati Business Courier this past year, including ‘Tech Company of the Year' and 'Best Device/Application.'

Predictronics was also featured on The Tech Tribune’s ‘2020 Best Startups in Cincinnati’ list, chosen by Tooploox as one of five startups for their ‘Top AI-Driven Predictive Maintenance Solutions of 2020,' recognized as a Product of the Year finalist in the Fourth Revolution Awards, and named a semifinalist in the Tech Ohio Startup Culture Awards.

Currently, Predictronics is a 2020 Product of the Year finalist for the Plant Engineering Magazine Awards. Check out our product profile and cast your vote for PDX to win.

Predictronics has proven our industry impact through numerous projects over the years. In 2020, we released seven new case studies, ranging in topics from predictive scheduling and predictive quality to virtual metrology and solutions for the freight and cargo industry. To view our case studies and learn more, click here. This past year, Predictronics hosted several webinars to demonstrate the benefits of our solutions for numerous applications, as well as showcase how these solutions are configured and deployed. These webinars focused on our solutions for predictive dynamic scheduling, automotive manufacturing, predictive quality, and semiconductor manufacturing.

Our CTO Dr. David Siegel was also a presenter during the smart manufacturing webinar hosted by the Japan External Trade Organization (JETRO), as well as co-host of two Control Engineering Magazine webinars, discussing successful deployments of AI-based solutions for predictive maintenance and machine learning for predictive quality solutions.