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What is Predictive Maintenance in Machinery about?

This study aims to apply machine learning techniques to predict faults in industrial machinery using two datasets - one for gearbox faults and one for rotary machinery faults. Various machine learning models including decision trees, random forests, AdaBoost, and deep neural networks were tested on the datasets. For the gearbox dataset, random forests and deep neural networks performed best with an F1-score and AUC of around 0.98. For the multi-class rotary machinery dataset, random forests outperformed wit

Author

jaimito13

Language

EN