Multistage Cost Estimation Framework for Transparent and Granular Bridge Maintenance

초록

Bridge maintenance cost is not an isolated variable but a constructed outcome derived from damage size, repair method, and unit cost. However, existing data-driven approaches often treat cost estimation as a black-box prediction problem, providing only aggregated cost values, without transparent and granular information. To address this knowledge gap, this study proposes a multistage cost estimation framework that explicitly structures maintenance cost estimation according to the fundamental construction management logic of quantity-method-price. The proposed framework sequentially estimates repair-required damage size, classifies appropriate repair methods, determines corresponding unit costs, and integrates these components to total maintenance cost. An extreme gradient boosting-based pipeline was developed using 3,716 inspection records from the Korean Bridge Management System and validated with 100 real-world bridge maintenance records. The results show that the proposed framework reduces the mean absolute error by 41.3% and 73.7% compared to conventional direct cost estimation models. By aligning data-driven modeling with the maintenance cost formation logic, this study advances bridge maintenance with more transparent and granular cost estimation.

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