Modelling and verification of TiO2/ZnO/EGW nano coolant on the tin milling tool performance - Lingenthiran, Samylingam (2019)
Surface roughness, tool life and wear mechanism plays major role for optimizing tool performance in machining process. Introducing nanoparticles into coolant has been proved to improve the optimization of the tool performance. This research has conducted to study the effect of nano particle based coolant (TiO2/EGW) and hybrid nano particle based coolant (TiO2/ZnO/EGW) on the Titanium Nitrate (TiN) tool enhancement. The linear model equation of surface roughness and tool life are developed using response surface methodology (RSM). From the RSM the most significant parameter is feed rate then axial depth of cut and lastly cutting speed. The end-milling operation by using hybrid nano particle based coolant (TiO2/ZnO/EGW) obtains lower surface roughness and high tool life. End-milling operation by using nano particle based coolant (TiO2/EGW) and water soluble coolant (EGW). Hybrid nano particle based coolant (TiO2/ZnO/EGW) lower the surface roughness 38% than EGW and 17% than TiO2/EGW. According to ISO 8688-2-1989 (E) the wear criteria for milling with water soluble coolant reached at average of cutting distance of 885 mm. Cutting distance for milling with nano particle based coolant (TiO2/EGW) performed better at distance of 55.55% to reach the wear criteria at average cutting distance of 1450 mm. Meanwhile for the cutting distance for milling with hybrid nano particle based coolant (TiO2/ZnO/EGW) perform better at 80% to reach the wear criteria at average cutting distance of 1585 mm. Hybrid nanofluid and single nanofluid’s thermal conductivity higher than EGW 13% and 11%.Hybrid nanofluid and single nanofluid specific heat capacity higher than EGW about 30% and 22%. The models between cutting parameters and response for surface roughness and tool life have been established. For surface roughness the error for the predicted value vs the actual value is 7%. Meanwhile for tool life the error for the predicted value vs the actual value is 11%. High cutting speed, low feed rate and low axial depth will provide fine surface roughness. Low cutting speed and Low feed rate will increase the tool life. The multi objective optimization for the parameters has been established. Where the optimum cutting speed= 2166 rpm, Feedrate = 0.02 mm/tooth and axial depth of cut = 0.1 mm which produces tool life = 37.07 min and surface roughness = 0.1452 μm. The desirability is nearly 1 (0.713), and it satisfy the goal of the optimization.