This working paper presents a data-driven framework for predictive maintenance and cost-informed planning of airport pavements. Using multi-airport pavement-condition data, it applies statistical and machine-learning models to forecast deterioration and support maintenance timing, lifecycle-cost analysis, and capital planning. The research demonstrates a reproducible approach designed for continued validation and application across U.S. airports.
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ESTHER OLUWADAMILOLA AINA (2026) studied this question.
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