Applying Innovative AI Techniques to Complex U.S. Army Datasets

As the amount of data that engineers and analysts needed to evaluate increases, the use of Artificial Intelligence (AI) techniques become more critical. Big data analytics tools can be used to find patterns and relationships within large data sets and the domain of Reliability, Availability, and Maintainability (RAM) for aircraft and missiles provides an ideal application for these big data methods. For aviation data, looking at relationships and patterns within and between maintenance events and on-board flight sensor data can provide added value for maintenance and logistics managers. For missile system data, looking at relationships and patterns within different collections of test data for the weapon system helps support important RAM decisions related to root cause analysis, the identification of reliability degradation trends, and the extension of missile shelf life. In this paper, the authors detail the integration of big data analytics tools and techniques to provide value to RAM stakeholders through the innovative analysis of aviation and missile datasets.