Data Mining within an Advanced Diagnostic and Prognostic System for Rotorcraft Maintenance

Qualtech Systems, Inc. (QSI), as a provider of model-based diagnostic and maintenance aiding tools, possesses key components required to implement many of the data analysis and decision-making functions required for on-line health management of largecomplex systems. Leveraging these capabilities, the proposed effort seeks to develop data mining capabilities required by reasoning systems to sustain seamless, distributed, multi-level health management and maintenance functions. Major innovations of thiseffort are the use of maintenance data mining results in flight-line maintenance activity to optimize troubleshooting strategies based on a combined analysis of onboard sensor data and fleet-wide history data, and customization to site-specific profile(available time, parts and maintenance resources, etc.). The data mining results will be made available via the Internet to the appropriate ground facility, contributing to significant benefits to current fleet operations and operational cost savings. ThePhase I effort will focus on enhancing QSI's knowledge base with a prototype capabilities for harvesting fleet-wide maintenance history and configuration data and analyzing it with a set of novel data mining techniques to update key parameters aidingfuture flight-line maintenance. The Phase I prototype capabilities will be developed in Phase II and interfaced with the Army's maintenance and logistics management systems.Aircraft maintenance and logistics management, health and usage monitoring ofaircraft, spacecraft, manufacturing processes and machinery, patient health monitoring