The aim of this project is the development of advanced software which integrates analytical and modeling tools for data mining, maintenance support, and structural health monitoring prognostics by incorporating Text Analysis and Concept Mapping for extracting new information from data represented as freeform text within documents and maintenance repositories. The project will develop new modeling, optimization tools and algorithm concepts that provide database search, concept linkage, and correlations facilitating intelligent decision making processes for maintenance, repair, and overhaul work practices and scheduling. Ultimately, such a support tool will act upon current databases, meta-data, and repair practices to arrive at considerable personnel, parts, and other resource savings as well as shorter repair time horizons within the Maintenance, Repair, and Overhaul (MRO) environment. An aircraft maintenance and repair work scope optimizer, as a decision support tool, will utilize dynamic data, meta-data information, and domain knowledge to provide the repair work force with a daily work package that accommodates contingencies via dynamic re-planning. The decision support tool will be orderly and repeatable; being controlled using advanced AI techniques to identify associations within a dynamic information repository, the Information Cube.
Meta-data mining for optimized aircraft repair and overhaul
Metadatengewinnung zur verbesserten Reparatur und Instandsetzung von Flugzeugen
2010
8 Seiten, 6 Bilder
Conference paper
Storage medium
English
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