Preparation and evaluation of carbon nano tube based nanofluid in milling alloy steel

Abstract

In machining, there is always a problem with heat generation and friction produced during the process as they consequently affect cutting force and surface finish. In the present decade, CNT water based nanofluids have become a promising new solution in high production machining because of its good fluidity and high thermal conductivity. This research work evaluates the performance of nano fluid using 0.3% volume of Single Walled Carbon Nano Tubes and 0.6% volume of Sodium Dodecyl Sulphate surfactant in deionized water for milling operation on 42CrMo4 steel material. Milling was performed without any fluid, with conventional Aquatex 3180 oil based cutting fluid and with nano fluid. The fluid was delivered through a specially designed and developed rotary liquid applicator designed in such a way so that it can deliver fluid at critical zones during surface milling. Cutting parameters in the machining process were cutting speed, table feed and depth of cut. Cutting forces and surface finish on work piece were measured as responses while turning under the three conditions and responses obtained in three different conditions of milling are compared. It is found that application of SWCNT based nano fluid resulted in maximum 33% lesser surface roughness than machining without any fluid whereas conventional cutting fluid resulted in 16% lesser surface roughness. The use of nano fluid also reduced cutting force by49% but conventional cutting fluid reduce the cutting force only by 26% with respect to dry milling. Thus, CNT-water based nano fluid performed better than the conventional, oil based cutting fluid for milling of 42CrMo4 steel. Finally, both ANN and RSM models were developed for prediction of cutting force and surface roughness as a function of cutting parameters. The models were proved to be successful in terms of agreement with experimental results and can be used in cutting process for efficient and economic production by forecasting the cutting force and surface roughness in surface milling operations.