Improved Electronics Maintenance through Tester Prognostics

Prognostics and health management (PHM) technology is critical for monitoring, detecting, and managing impending faults and enabling proactive maintenance of electronic systems before actual failures occur. This is essential to enhancing weapons systems reliability and maintaining a high level of mission readiness and affordability. Current PHM advancements have focused on developing physics based and data driven models to enable the predictive capability. There is a need to integrate these advancements with Automatic Test Equipment data. This effort investigates the development and application of a toolset to enable the integration of data produced by the electronic system (BIT, on-system diagnostics) with data produced by health assessment models and algorithms and data from ATE test results- for system-level prognostics and health management of electronic systems. The effort researches and characterizes a systematic framework for the integration, processing, distribution and management of health state data across multiple networked ATE systems and multiple maintenance organizations. This effort includes investigating the application and enhancement of the latest IEEE ATS-related standards such as ATML to provide a structure for capturing, exchange and management of health state data and information across the maintenance infrastructure. A proof-of-concept demonstration for a small target system is part of this effort.