Maintenance Decision-Making under Prognostic and Diagnostic Uncertainty Task SMM 0301

1. Maintenance Decision-Making under Prognostic and Diagnostic Uncertainty Task SMM 0301 Project Team Principal Investigator C. Richard Cassady, Ph.D., P.E. Co-Principal Investigators Heather L. Nachtmann, Ph.D. Edward A. Pohl, Ph.D. Graduate Research Assistants Alejandro Mendoza Undergraduate Research Assistants Nick Rew, Mauricio Carrasco, Lauren Chambers, Jason Honeycutt Project Activities • Define the system structure and reliability characteristics of each component in the system • Identify characteristics of prognostic and diagnostic tools • Develop a mathematical model that will provide an assessment of the system • Use USAF information to assess the potential for this methodology Project Motivation • Uncertainty in prognostic and diagnostic information provided to maintenance technicians • accuracy/precision of tools • inconsistencies across tools • Resulting incorrect maintenance actions • omissions and commissions • additional delays Project Objective To develop a methodology based on mathematical modeling that can be used to synthesize the prognostic and diagnostic information and provide a recommended course of action Generic Problem • Imperfect diagnostic tools lead to errors in problem diagnosing • Two types of errors can occur: • false positive- saying a component is in bad condition when it is good • false negative- saying a component is good when it is bad Modeling • Utilize probability theory and artificial neural networks • Develop a model so that prognostics and diagnostics information can be input, and a system assessment will be given from this implementation Application Identify a USAF system for analysis Tailor modeling to this system Use historical data to assess our approach Approved for Public Release, HEA-04-033