TY - JOUR
T1 - Multi response parametric optimisation in machining of marine application based GFRP composite with HSS drill
T2 - 2nd International Conference on Advances in Mechanical Engineering and Nanotechnology, ICAMEN 2020
AU - Bhat, Ritesh
AU - Mohan, Nanjangud
AU - Sharma, Sathyashankara
AU - Kini, Achutha U.
AU - Shivakumar, Shivamurthy
AU - Naik, Nithesh
PY - 2020/1/1
Y1 - 2020/1/1
N2 - The article aims at the optimization of the speed, feed and composite laminate thickness of glass fiber reinforced polyester composites. The composite studied is made up of isophthalic polyester resin and chopped E-glass fiber, which is primarily made use in marine applications. The drilling experiments are conducted using the HSS tool of 10 mm diameter, fixed in the computer numerically controlled vertical machining center. The surface integrity and surface morphology issues are considered as the response variables and quantified by delamination factors and surface roughness, respectively. The technique for order of preference by similarity to ideal solution is used for multi response optimization, wherein the performance index is determined as the function of all the selected response variables. The regression model is developed using MINITAB 19 for the performance index, which exhibits an exceptionally high degree of fitness with an average prediction error of 5.72% between the predicted and the experimental values. The selected technique proves to provide better and clear results while considering the correlation between the response variables.
AB - The article aims at the optimization of the speed, feed and composite laminate thickness of glass fiber reinforced polyester composites. The composite studied is made up of isophthalic polyester resin and chopped E-glass fiber, which is primarily made use in marine applications. The drilling experiments are conducted using the HSS tool of 10 mm diameter, fixed in the computer numerically controlled vertical machining center. The surface integrity and surface morphology issues are considered as the response variables and quantified by delamination factors and surface roughness, respectively. The technique for order of preference by similarity to ideal solution is used for multi response optimization, wherein the performance index is determined as the function of all the selected response variables. The regression model is developed using MINITAB 19 for the performance index, which exhibits an exceptionally high degree of fitness with an average prediction error of 5.72% between the predicted and the experimental values. The selected technique proves to provide better and clear results while considering the correlation between the response variables.
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U2 - 10.1016/j.matpr.2020.03.227
DO - 10.1016/j.matpr.2020.03.227
M3 - Conference article
AN - SCOPUS:85088402345
SN - 2214-7853
VL - 28
SP - 2077
EP - 2083
JO - Materials Today: Proceedings
JF - Materials Today: Proceedings
Y2 - 28 February 2020 through 29 February 2020
ER -