MODUS OPERANDI, INC. — Department of Defense SBIR Phase I: A20-115

Description

The overarching goal of this effort is to integrate M/L analytics and a human machine interface that deliver to logistics analysts the optimal knowledge for minimizing missile system downtime and maximizing system availability.  The technology will advance sustainment via data-driven analytics and advanced diagnostic capabilities supplying a UI for dynamic inputs for real-time result analysis.  The developed algorithms will preprocess the legacy data to find trends, outliers, or anomalies in the data and suggest optimal AI/ML analysis. The project will demonstrate performance and scalability of the proposed approach, providing a clear path for technology transition into Army missile and related logistics programs applicable DoD-wide. Application of the developed analytical software to the data will surface previously unknown root causes of substandard performance or system downtime providing immediate actionable items.   Our vision for OPTIMIST is applied deep learning, AI/ML analytics and real-time computational intelligence to provide fact-based evidence to support the optimal missile lifecycle maintainability. The end state of our Phase I research project will be the design of a compelling proof of concept that applies OPTIMIST technology and meets objective sustainment metrics for optimal support achieving a significant reduction in data processing time over current methods.