Predictive Maintenance in Logistics Fleets: A Comparative Evaluation of Random Forest, XGBoost, and Logistic Regression Using Operational and Technical Indicators
Background: Predictive maintenance (PdM) is increasingly recognized as essential for reducing fleet downtime and maintenance costs, yet the existing literature on transport and logistics fleets relies predominantly on traditional or single-model approaches, with ensemble methods such as random forest and gradient boost...