This grant provides funding for developing a sensory-based prognostic methodology for predicting failures of complex systems, such as manufacturing systems, nuclear plants, military systems, and others. The proposed methodology will integrate system-specific information acquired through sensory monitoring technology, and the general reliability and durability characteristics of a system. The reliability knowledge will provide preliminary failure time estimates. Real-time system-specific information, in the form of degradation-based sensory signals, will be used to continuously update these estimates and provide accurate remaining life predictions based on the unique performance of the system and its components. This will be achieved be correlating the evolution of the degradation signals with the underlying physical transitions that occur prior to failure. The proposed methodology also captures the effects of time-varying operating and environmental conditions on degradation and failure processes. These dynamically evolving remaining life predictions will then be integrated with maintenance and spare parts logistics models to provide a factual sense and respond paradigm. These developments will be validated using laboratory testing platforms, industrial case studies that include construction and agricultural equipment, electronics, and avionics systems, and military applications that include Navy aircraft power systems and others.
The research developments target the prevention of unexpected failures. The success of this research will positively impact the effectiveness of engineering systems in the manufacturing and service sectors, health care, and national security, among others. The research will support ongoing national initiatives like the "Next Generation Manufacturing Technology Initiative". Advances in "biosensors" will enable the implementation of these findings in health care applications and will improve human safety. From an educational standpoint, the infusion of the proposed developments into the curriculum will present graduate and undergraduate students with a contemporary view of reliability and maintenance logistics, and will provide a rich variety of research opportunities.
