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K. Thongkaew

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Open access Sep 2026

Machine Learning–Driven Predictive Maintenance for Smart Beverage Manufacturing Systems

The Random Forest model was the best performer, achieving an accuracy of 0.990, precision of 0.918, recall of 0.722, F1-score of 0.808, and ROC-AUC of 0.995 at the optimized threshold of 0.45, demonstrating a practical trade-off between reducing missed breakdown warnings and avoiding excessive unnecessary inspections.

Peerawit Pongtananikorn, K. Thongkaew · 0 citations

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