A Collaborative Environment for Data Driven Condition Based Maintenance

This Phase II SBIR proposal presents a new platform for development, validation, and deployment of health and status assessment and decision support applications. At the core of this platform is MSI’s Collaborative Bayesian Application Engineering Environment (CBAEE) for developing models supporting signature recognition, condition assessment, and decision support. This Collaborative Engineering Environment provides graphical model construction, automated model calibration and structure learning, statistical data analysis, and automated model validation. It supports development of robust high performance statistical models that combine information from signature recognition with dynamic trending and auto-correlation analysis. MSI has teamed with Boeing Corporation to develop, integrate, and test health assessment and decision support applications for the Airborne Laser weapon system. This system will process signature data, operating logs and other data that characterize the operating condition of equipment. The two year Phase II contract has several goals: 1) to system engineer a robust Collaborative Bayesian Model Engineering Environment, 2) to develop the software applications for health monitoring and decision support using this toolkit, 3) to test and validate these applications with ABL equipment data and signatures in conjunction with the ABL operations, support and maintenance teams, and 4) to transition the toolkit for use by MDA and DoD programs.