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Predicting the Tool Wear of a Drilling Process Using Novel Machine Learning XGBoost-SDA

Tool wear negatively impacts the quality of workpieces produced by the drilling process. Accurate prediction of tool wear enables the operator to maintain the machine at the required level of performance. This research presents a novel hybrid machine learning approach for predicting the tool wear in...

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Detalles Bibliográficos
Autores principales: Alajmi, Mahdi S., Almeshal, Abdullah M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7663048/
https://www.ncbi.nlm.nih.gov/pubmed/33158099
http://dx.doi.org/10.3390/ma13214952