Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/2690
Title: | Prediction of Vibration Amplitude and Surface Roughness in Boring Operation by Response Surface Methodology |
Authors: | Yuvaraju, B A G Nanda, B K |
Keywords: | Analysis of Variance (ANOVA) Boring Bar Box-Behnken design Composites Surface roughness (Ra) Response surface methodology Vibration amplitude |
Issue Date: | Mar-2017 |
Publisher: | Elseiver |
Citation: | International Conference on Emerging Trends in Materials and Manufacturing Engineering (IMME17), NIT), Tiruchirapalli, India, 10-12 March 2017 |
Abstract: | Vibrations produced in machine tools like lathe, milling and grinding, etc. during machining operation are one of the primary concern in manufacturing industries. These vibrations not only increase the surface roughness of workpiece but also affect the tool life and noise during the machining operation. In this paper, the effect of input variables viz. speed, feed and depth of cut on output responses such as the vibration amplitude of boring bar and surface roughness of workpiece in boring operation has been studied by providing different composites under the tool using response surface methodology (RSM). The design matrix is created by Box-Behnken design (BBD) with three center points and a single block by three-factors of each three-level to perform the experiments with two different composites such as glass fiber reinforced epoxy (GFRE) and glass fiber reinforced polyester (GFRP). Also, mathematical models have been developed for the output responses as a function of input variables. The developed models have been verified using analysis of variance (ANOVA). Further, the predicted models have been verified by performing the confirmation experiments. It has been found that there is a reduction in surface roughness as well as vibration amplitude with an increase in the number of composite plates placed under the tool |
Description: | Copyright for this paper belongs to proceeding pubisher |
URI: | http://hdl.handle.net/2080/2690 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2017_IMME17_BAGYUvaraju_Predication.pdf | 493.12 kB | Adobe PDF | View/Open |
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