Exploring the Potential of Integrating Machine Tool Wear Monitoring and ML for Predictive Maintenance - A Review
Keywords:
Machine tool, Wear monitoring, ML, Predictive Maintenance, sensors, costs, performanceAbstract
This research review article explores the potential of integrating machine tool wear monitoring and ML algorithms for predictive maintenance. It synthesizes the latest research in the field, while discussing the benefits and challenges of various approaches. Specifically, this review examines the applications of sensors in machine tool condition monitoring, the use of ML algorithms to detect wear patterns and predict maintenance needs, and the potential of integrating ML and predictive maintenance. The article also evaluates the potential of using ML algorithms in conjunction with sensor data to improve tool performance and reduce maintenance costs. Finally, the article provides scope for future research to expand the potential of ML for predictive maintenance in machine tools. Overall, this review highlights the potential of integrating ML with predictive maintenance for machine tool applications.
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