Non-Instrumented Individual Asset Tracking of Severity Exposure

Abstract Traditional methods for corrosion inspection and maintenance of aircraft are schedule-based processes with minimal consideration for actual corrosion severity and individual aircraft conditions. Corrosion processes are dependent variable environmental conditions, material properties and combinations, and structural and component details. Therefore, conventional maintenance practices may be overly conserved but still not capture outlier conditions that cause corrosion degradation of aircraft structures and systems. A shift toward evidence-based and data-driven predictive maintenance could improve efficiency and reduce total ownership costs. Individual aircraft tracking of the environmental severity could accomplish this goal. In this work, an automated approach for tracking asset severity was developed, needing only an input of the flight records (location, date, and asset ID). The novel approach leverages correlations between corrosion and environmental measurements to classify severity and calculate cumulative severity and corrosion degradation risk for an individual asset. The framework and methodology developed for aerospace applications can be applied to automotive or marine vessel severity tracking. The algorithms and predictive results were validated throughout the development.