Sponsor:

Air Force Research Laboratory

Research Team:

C. Richard Cassady, Jason Honeycutt, Mauricio Carrasco , Alejandro Mendoza, Edward A. Pohl, Lauren Chambers, Nick Rew

Universities Involved:

University of Arkansas

Start Date:

09/05/03

End Date:

01/29/05

Summary:

This project defines system structure an component reliabilit characteristics, Identifies characteristics of prognostic and diagnostic too, develops mathematical model, and incorporates model into a decision-support environment
A key challenge faced by USAF maintenance personnel is the imperfection of aircraft prognostic and diagnostic capabilities. These imperfections include an inability to pinpoint failed components, the incorrect identification of failed components, and “cannot-duplicate” errors between the flightline and the depot. In addition to lower morale in maintenance personnel, these imperfections lead to increased delays in returning aircraft to the fleet and excessive requirements for spare parts in the supply chain. Unfortunately, it is difficult to assess the impact of improvements on prognostic and diagnostic capabilities. The objective of this project is to develop a methodology based in mathematical modeling for analyzing these impacts. Specifically, we intend to address the following questions: (1) What impact do prognostic and diagnostic errors have on fleet readiness and the associated requirements for spare parts investment? (2) Given a specific investment in prognostic and diagnostic improvements, what will the impact be on fleet readiness and spare parts inventory measures? (3) Given a limited budget for prognostic and diagnostic improvements, how should the funds be allocated to optimize fleet readiness and spare parts inventory measures?