Please use this identifier to cite or link to this item: https://doi.org/10.1109/EFTA.2007.4416766
Title: Model-based monitoring and failure detection methodology for ball-nose end milling
Authors: Huang, S.
Goh, K.M.
Chuan, K.
Wong, Y.S. 
Hong, G.S. 
Issue Date: 2007
Citation: Huang, S.,Goh, K.M.,Chuan, K.,Wong, Y.S.,Hong, G.S. (2007). Model-based monitoring and failure detection methodology for ball-nose end milling. IEEE International Conference on Emerging Technologies and Factory Automation, ETFA : 155-160. ScholarBank@NUS Repository. https://doi.org/10.1109/EFTA.2007.4416766
Abstract: This paper presents a model-based monitoring and failure detection approach in ball-nose end milling process. A mechanistic force model has been established for high speed milling on hardened stavax steel with 6mm micro-grain tungsten carbide 2 flute ball-nose end mill. The threshold curve can be obtained off-line based on the process model as the cutting engagement conditions along the tool path are determined at the simulation stage. The measured cutting forces are monitored on-line to detect the faults by comparing them with the threshold curve at machining stage. If a fault is detected at certain position along the tool path, an intelligent predictive method developed in [1] is utilized to predict whether this fault will result in catastrophic failure. Experimental results are provided to demonstrate the feasibility of this approach. © 2007 IEEE.
Source Title: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
URI: http://scholarbank.nus.edu.sg/handle/10635/51625
ISBN: 1424408261
DOI: 10.1109/EFTA.2007.4416766
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