CMA Technologies

Advanced Analysis Software Research and Development

CMA’s software Research and Development capability is focused on providing answers to help customers make well informed decisions through complex analysis. We combine experience in developing applications, databases and user interfaces with advanced analysis techniques that include novel fault tree applications, deep learning and statistical principles.

CMA’s Functional Defeat Analysis Tool (FDAT) was designed to help warfighters and weapon developers make sense of the wide variety of emerging attack capabilities to obtain functional defeat of hard and complex targets. FDAT uses a unique dynamic fault tree approach analyze effects of conventional, non-lethal, non-kinetic, and other attack capabilities to meet defined functional defeat objectives. By employing deep learning and specialized optimization techniques, FDAT determines the optimal mix of weapons, strike order and restrike to meet functional defeat objectives with the minimum number of sorties.

CMA’s Supply Chain Risk Analysis Model (SCRAM) extended dynamic faults tree methodologies to analyze risks across complex supply chains. SCRAM gives supply chain managers a quantitative evaluation of 24 different risks across their entire supply chain to determine which parts and which risks are most likely to result in supply chain disruptions. This allows supply chain managers to be proactive in addressing problems before they are encountered. SCRAM includes a Pareto optimizer that determines the optimum use of inventories to give the greatest risk reductions for the lowest possible investment.

CMA has also developed and delivered Proper Orthogonal Decomposition software tools to give users near-CFD levels of analysis accuracy in near-real time based on developing a limited number of CFD runs across the analysis space of a problem. This gives analysts and software integrators the capability to explore a wide range of operational parameters in a fraction of the analysis time. These techniques are highly applicable to system design and optimization and hardware in the loop system response analysis.