Prognostics and Health Management (PHM) is an approach that is used to evaluate the reliability of a system in its actual life-cycle conditions, determine the initiation of failure, and mitigate system risks by using artificial intelligence for fault diagnosis and forcasting fault progression. Prognostics of a system can yield an advance warning of impending failure in a system and thereby help in maintenance and corrective actions, which prevents catastrophic failures and reduces unscheduled maintenance expenses. In addition to stochastic models, sophisticated machine learning and deep learning algorithms are used for remaining useful life prognostics of an engineering system, subsystem or even a component. - The Joint Strike Fighter Program requires PHM
- NASA uses the Integrated Vehicle Health Management program for its fleet
- GE uses PHM on its engines, wind turbines, and medical instruments
- GM uses PHM to on its vehicles as part of its OnStar system
- Dell, Apple, Samsung, and Intel invested millions in prognostics research
This graduate course at the University of Maryland is one of the few in academia that covers the concepts and theory of PHM along with the latest applications. Students will learn the fundamentals and be able to apply the latest methods and tools. Guest speakers from organizations, such as Case Western Reserve University, Dell, Medtronics, NASA, SAP, and Western Digital, will cover areas of application. Online students can attend the lectures live or stream the videos for watching anytime. D.C. CONSORTIUM students are also eligible. Others outside of UMD and the consortium universities need to get admission as a non-degree seeking student to register for the class. |