GRA based optimization of tool vibration and surface roughness in face milling of hardened steel alloy

In current study, an experimental research has been carried out for the enhancement in process variables during the machining of EN31 steel. Although the effect of the process parameters such as cutting speed, feed rate and depth of cut on responses like surface roughness has been presented by many...

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Bibliographic Details
Main Authors: Singh, Talvinder, Sharma, Vijay Kumar, Rana, Mohit, Singh, Kamaljeet, Saini, Abhineet
Format: Conference Proceeding
Language:English
Subjects:
Grey relational analysis
Minimum quantity lubrication
Surface roughness
Taguchi orthogonal array
Tool vibration
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Summary:In current study, an experimental research has been carried out for the enhancement in process variables during the machining of EN31 steel. Although the effect of the process parameters such as cutting speed, feed rate and depth of cut on responses like surface roughness has been presented by many researchers, still there is a scope of improvement in determining effect of these process variables using an appropriate multi-response optimization technique. Along with the machining parameters, cooling concentration in terms of minimum quantity lubrication (MQL) is also considered. The output responses viz. surface finish achieved during machining and the effect of tool vibration are evaluated. A comprehensive analysis between the input parameters and output responses by using hybrid optimization technique consisting of Taguchi based orthogonal array (TGRA) and grey relational analysis has been accomplished.
ISSN:2214-7853
2214-7853
DOI:10.1016/j.matpr.2021.09.546