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Data-Driven Maintenance Optimization: Aligning Prognostic Learning with Decision Objective
Estimation error in machine learning prognostic models can propagate into poor maintenance decisions. We study a data-driven predictive maintenance problem coupling health-condition estimation with a joint ordering-replacement model. We show that the conventional Estimate-Then-Optimize (ETO) approac
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