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Optimization of Machining Parameters in End Milling of AISI H11 Steel Alloy by Taguchi based Grey Relational Analysis


Author : Nikhil Aggarwal and Sushil Kumar Sharma

Pages : 2797-2803
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Abstract

This study investigated the effects of the machining parameters by end milling operation on the AISI H11 steel alloy. Metal machining has been a very significant activity in manufacturing. Surface quality is one of the most common concern is to satisfy customer needs in which the major indication of surface quality on machined parts is surface roughness. It has long been recognized that the machining conditions, such as cutting speed, feed and depth of cut affect the performance of the operation to a high extent. Surface roughness and material removal rate should be taken into consideration. This can be achieved using design of experiments (DOE). It is used in the manufacturing industries for making die casting moulds, extrusion dies, moulds for glass industry, punches, etc. In the present study the machining experiments were conducted on CNC vertical milling machine whose maximum speed was 6000 RPM. Design of experiments based on Taguchi grey relational analysis with three independent factors (cutting speed, feed rate and depth of cut), three levels L27 orthogonal array has been used to develop relationships for predicting surface roughness and metal removal rate. The surface roughness was measured using surface roughness tester (Mitutoyo surftest-4) and the averages were calculated to obtain the surface roughness of the samples. Material removal rate was calculated using the formula in terms of width of cut, depth of cut and table feed rate.

Keywords: Grey Relation Analysis, ANOVA, DOE, Surface Roughness and Material Removal Rate

Article published in International Journal of Current  Engineering  and Technology, Vol.4,No.4 (Aug- 2014)

 

 

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