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 system availability and maintaining a high level of mission readiness and system affordability. Current PHM advancements have focused on developing physics based and parametric data driven models to enable a predictive analytics capability. There is a need to integrate these advancements with Automatic Test Equipment data. This effort covers 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 is focused on developing a system health record (SHR) framework for the collection, integration, processing, distribution and management of health state data across multiple networked ATE systems and multiple maintenance organizations. This effort includes 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.
Benefit: The technology developed under this effort can be easily applied in other domains such as commercial aviation, sea, space and ground vehicle platforms, in order to advance the implementation of Condition Based Maintenance (CBM+) principles. In addition, there is a big potential for commercialization. For example, the technology resulting from this effort can be applied in other industries including, commercial aviation, power utilities, automotive, consumer appliances, medical equipment, and any commercial plants where failures in large scale manufacturing systems have a great economic impa
Keywords: Electronics System, System Health Record, PHM, Diagnostics, Prognostics, Model Maturation, PHM Ontology, Health monitoring, automatic test system