%0 Journal Article
	%A Kious Mecheri and  Hadjadj Abdechafik and  Ameur Aissa
	%D 2014
	%J International Journal of Electrical and Computer Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 87, 2014
	%T Neural Network Monitoring Strategy of Cutting Tool Wear of Horizontal High Speed Milling
	%U https://publications.waset.org/pdf/9997741
	%V 87
	%X The wear of cutting tool degrades the quality of the product in the manufacturing processes. The on line monitoring of the cutting tool wear level is very necessary to prevent the deterioration of the quality of machining. Unfortunately there is not a direct manner to measure the cutting tool wear on line. Consequently we must adopt an indirect method where wear will be estimated from the measurement of one or more physical parameters appearing during the machining process such as the cutting force, the vibrations, or the acoustic emission etc…. In this work, a neural network system is elaborated in order to estimate the flank wear from the cutting force measurement and the cutting conditions.

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