Proactive Methodology for Identifying Problem Aerospace Parts

ABSTRACT: Accurate prediction of part performance/reliability is at the core of health management of air vehicles and of supply chain management. Methodologies are needed to accurately predict/evaluate parts performance/reliability with compounding problem criteria/factors for early corrective actions and acquisition of aerospace parts. Accurate problem part (bad actor) identification and resource allocation (prioritization) is a tedious and difficult undertaking for engineers and equipment specialists. This project is to implement the BIPS engine (Bad actor Identification and Prediction for Sustainment) which will encapsulate the essential subcomponents. BIPS components are identification (current problem parts), inference (determination of secondary effects), and prediction (determination of parts that are expected to reach bad actor status eventually). BIPS will be modeled as an open architecture to fit within a changing lifecycle. BENEFIT: The technology produced during the Phase II will provide solution to an important problem, that is identification of problem parts. The software developed could be used in the areas of commodities and engines. It has a very high commercialization potential.