Methodologies for Integration of Prognostic Health Management Systems with Maintenance Data

Prognostic techniques are intricately tied to the physics of incipient-fault-to-failure progression, and hence most prognostics research has focused on developing techniques for a range of components such as rotating machinery parts. The research and development of such techniques has relied on the theories of material science, structural mechanics, domain expertise, as well as empirical studies such as accelerated run-to-failure testing. Even after prognostic models have been developed and operationally validated for various components of a system, the challenge remains how prognostic assessments from individual components of a system (such as the aircraft engine) should be used to make maintenance and logistics decisions. QSI proposes to perform the research and development needed to bridge the gap between the individual component prognostics and the system-level reasoning required to support maintenance and logistics decisions. To strengthen this effort, QSI is teaming with SMI for their expertise in prognostics and logistics decision support and Vanderbilt for expertise in material failure progression modeling and diagnostics. The team is further strengthened by two OEMs: Pratt and Whitney as the engine prime and Boeing as an airframe prime to ensure that the effort retains relevance and applicability to the acquisition program sponsoring this SBIR.