Corrosion significantly impacts1 safety, availability and sustainment costs of U.S. Air Force (AF) systems and equipment. System downtime due to corrosion maintenance decreases the availability of systems to perform their National defense mission and drives the need for more aircraft and associated logistics tail. In addition, the AF spends about $5.5 Billion per year, about 21 percent of the annual AF maintenance budget, on corrosion maintenance. This cost exceeds the annual Pentagon budget for the campaign against the Islamic State.2 Because of these significant impacts, AF leaders need reliable maintenance data and analytical tools to make decisions to reduce the impact of corrosion maintenance.

This paper proposes that AF maintenance leaders adopt decision-making model that is built upon metrics developed by LMI3 to prioritize opportunities for data-driven corrosion maintenance decisions. The LMI metrics methodology uses top-down and bottom-up approaches to converge on an accurate estimate for corrosion-related availability and maintenance cost. The top-down approach starts with DoD-wide data systems then uses a process of elimination to yield AF corrosion maintenance costs. The bottom-up approach aggregates labor and material cost data from maintenance records, using an algorithm or “recipe” developed jointly with AF maintenance experts, to yield availability and cost data. LMI bridges gaps between the top-down and bottom-up totals by applying statistically valid scaling factors.

The resulting metrics feed a corrosion decision-making model that includes performance monitoring, corrosion problem identification, analysis of options, and selecting and launching solutions. The proposed decision-making model and metrics will enable stakeholders to make data-driven assessments of which subsystems and maintenance activities to investigate for potential corrosion maintenance improvements.

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