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A data-driven prognostics framework for tool remaining useful life estimation in tool condition monitoring.

, , , , , , and . ETFA, page 1-8. IEEE, (2017)

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Hidden Markov model-based predictive maintenance in semiconductor manufacturing: A genetic algorithm approach., , , , , , , and . CASE, page 1260-1267. IEEE, (2017)Power-signature-based Bayesian multi-classifier for operation mode identification., , , , and . ETFA, page 1-6. IEEE, (2016)Generating Pool of Classifiers with Hyper-Parameter Optimization for Ensemble., and . IECON, page 1-6. IEEE, (2021)Predictive maintenance decision using statistical linear regression and kernel methods., , , and . ETFA, page 1-6. IEEE, (2014)Accelerating Task Completion in IIoT Based Smart Factory Through Optimal Restart., , and . IECON, page 1-6. IEEE, (2021)Online predictive maintenance approach for semiconductor equipment., , , and . IECON, page 3662-3667. IEEE, (2013)A data-driven prognostics framework for tool remaining useful life estimation in tool condition monitoring., , , , , , and . ETFA, page 1-8. IEEE, (2017)Remaining Useful Life Prediction Using Time-Frequency Feature and Multiple Recurrent Neural Networks., , , and . ETFA, page 916-923. IEEE, (2019)Kernel-based SMOTE for SVM classification of imbalanced datasets., , , and . IECON, page 1127-1132. IEEE, (2015)A Multi-State Diagnosis and Prognosis Framework with Feature Learning for Tool Condition Monitoring., , , , , , , and . CoRR, (2018)