On-board, Prognostic Micro-Structural Reliability Tool for Mechanical Systems

Technology for extending the life of fielded systems offers the potential for signification savings in total ownership costs. Through on-board monitoring and analysis, our technology will instill increased confidence in prediction of fatigue or remaininguseful life. This, in turn, offers the potential to reduce premature part retirement and thus shifting part replacement costs to the out-years. Advancement in prognostics and health management is a significant thrust within the JSF engine developmentprogram. This proposal exactly corresponds with the JSF key technology maturation program for prognostics & health management whose stated goal is on reducing maintenance manpower.However, the current state-of-the-art does not take advantage of the developed or newly developing microstructural material modeling capabilities that allow for prediction of crack initiation and growth resulting in pending component failure. The Phase Iproject will demonstrate the feasibility for using sensed data to generate, on-board, mechanical systems reliability prediction based on analysis of microstructural based probabilistic modeling techniques. Upon demonstrating feasibility, Phase II willfurther develop the technology and apply this on-board prognostics technology on an actual engine component. This technology will serve to provide real-time or near real-time insight into how material microstructure level changes effect the overallreliability of a mechanical system. Using our product, aerospace or maintenance engineers will know what systems must be identified for upgrade and/or replacement. On the other hand, DoD will benefit from the fact that some replacements or repairs may bedelayed, thus effectively extending the lives of some mechanical systems.The technology proposed herein offers the potential to reduce the total ownership cost for the emerging JSF family of aircraft. Eventually this prognostic technology will be installed on aircraft systems and allow for on-board reliability prediction.