Collaborative Multidiscipline Digital Circuit Board Prognostics and Health Management

This project explores new methods that can dramatically improve the ability to accurately predict the useful life remaining for individual digital printed circuit boards at any particular point in time. The proposed capability will improve the system maintainers’ ability to identify marginal circuit boards and components, and to replace them prior to actual failure in the field to prevent mission compromise. Our approach encompasses the novel use of new technology that supports sensor-fusion spanning the DC to EHz range of the electromagnetic spectrum enabling maintainers to visualize both electrical and physical changes within these digital circuit boards that are indicative of pending failure, long before their actual failure in the field. This is accomplished by providing maintainers with extremely high resolution imagery of the inner constructs of electronic printed circuit board components, solder connections and the PCB itself to visually identify marginal components, developing defects and identified/untested failures. In addition, computer algorithms also examine these images to detect the presence of prognostic indicators of future or pending failure. Such phenomena can neither be detected nor modeled using today’s conventional test program set (TPS) and automatic test equipment (ATE), however, this capability provides clear indication of events suitable for prognostic purposes.