Tool condition monitoring in interrupted cutting with acceleration sensors |
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| Affiliation: | 1. University of Žilina, Faculty of Mechanical Engineering, Univerzitná 1, 010 26 Žilina, Slovakia;2. VŠB-Technical University of Ostrava, 17. listopadu 15, 70833 Ostrava, Czech Republic;1. Assistant Professor, Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India;2. Adjunct Professor, Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India;3. Professor, Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112, India;1. Department of Mechanical Engineering, McGill University, Montreal, QC, Canada;2. Aerospace Manufacturing, National Research Council Canada, Montreal, QC, Canada;1. Manufacturing System Integration, Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;2. Department of Engineering Design and Manufacture, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia |
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| Abstract: | Tool breakage is a serious issue in conditions with highly variable stress such as interrupted turning. The tool may fail suddenly though commonly tool failure is preceded by other symptoms such as chipping or fracture of tool edges and tool wear before the complete failure. These symptoms can be used to predict reliably complete tool failure. In the case of a complete failure, the surface integrity of the workpiece is commonly ruined causing waste, making the individual events one of the most expensive failures in small series and flexible manufacturing in addition to collisions. In earlier studies, tool wear has been monitored by force sensors. There are also methods for estimating cutting force with acceleration sensors. In this study, it is demonstrated that it is possible to estimate tool deflection, connected to main cutting force, with acceleration sensor and use this information for detecting the chipping and small fracture of the tool edge. The method presented in this study can be used as a predictor for complete tool failure and thus prevent waste. |
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| Keywords: | Tool condition monitoring Turning Interrupted cutting Acceleration sensors Process monitoring |
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