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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/100/17411

Title: Modeling of machined surface quality in high-speed ball-end milling of Inconel-718 thin cantilevers
Authors: SONAWANE, HA
JOSHI, SS
Keywords: WALLED WORKPIECES
ROUGHNESS
PREDICTION
PARTS
Issue Date: 2015
Publisher: SPRINGER LONDON LTD
Citation: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 78(42259)1751-1768
Abstract: Machining of thin flexible parts in the aerospace and power industries often involves workpiece deflection majorly influencing the machined surface quality. Very few attempts have been done so far to address issues in the ball-end milling of thin cantilever-shaped parts made of "difficult-to-machine" materials. The objective of this paper is to optimize the machining parameters under the design constraints such as workpiece thickness, workpiece inclination, and cutter orientation to get the best possible machined surface quality. Accordingly, correlations between surface quality and the workpiece deflection have been developed. Independent variables were optimized using a central composite design (CCD) with each variable taken at five levels. All the results were compared with the results obtained by the ball-end milling on flat and horizontal cantilever without an inclination. Analytical models have been developed to predict the instantaneous workpiece deflection, undeformed chip thickness, and width of cut and correlated them with the machined surface quality. The lowest surface roughness of similar to 1 mu m Ra was obtained at a higher cutting speed of 120 m/min and a lower feed rate of 400 mm/min, on thicker workpiece (> 5 mm) inclined at an angle of 45A degrees along with the horizontal outward cutter orientation. The dimensional accuracy (width of cut) and the workpiece deflection can be predicted more accurately during ball-end milling of thicker Inconel-718 workpiece inclined at higher angles.
URI: http://dx.doi.org/10.1007/s00170-014-6759-6
http://dspace.library.iitb.ac.in/jspui/handle/100/17411
ISSN: 0268-3768
1433-3015
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