Optimization of process parameters in micro milling of Ti4Al4Mo2Sn using nano Al2O3 additives based minimum quantity cooling lubrication

Abstract

ABSTRACT. Aerospace and automotive industries employ Ti₄Al₄Mo₂Sn material in many applications due to its properties of better strength to weight ratio and high corrosion resistance. Ti₄Al₄Mo₂Sn finds itself difficult to cut materials due to its physical and chemical properties and is prone to more heat generation during machining. The more generation of heat affects the machined material surface quality and other related properties. In this investigation, the thermal conductivity and stability of Al₂O₃/Water based nanofluids are studied to select the best composition of nanofluid for transferring heat. The thermal conductivity and stability of the nanofluid for a duration of 30 days are computed by employing the KD2 thermal property meter and pH meter, respectively. Thermal conductivity and stability of the Water/4.5 vol.% Al₂O₃ nanofluid are found to be better than other combination of nanofluids. In the present study, optimizing the micro milling process parameters on Ti₄Al₄Mo₂Sn material with Minimum quantity cooling lubrication (MQL) is focused. The input parameters selected for this micro milling process are spindle speed, feed rate, depth of cut and Water/4.5vol.% Al₂O₃ nanofluid and the output parameters selected are cutting forces in X(F_x) and Y(F_y) directions, tool wear rate (TWR) and surface roughness (SR). The optimization is done with the help of grey relational analysis (GRA) by using L9 Orthogonal Array (OA) Taguchi design. The obtained sequence of influencing parameters are feed rate per tooth, Al₂O₃nanofluid, spindle speed and depth of cut. The percentage of grey relational grade (GRG) for prediction and experimental is 0.721 and 0.957. The percentage of improvement of GRG is 12.46.

KEY WORDS: Ti₄Al₄Mo₂Sn, Al₂O₃, Thermal conductivity, Grey relational analysis, Grey relational grade

Bull. Chem. Soc. Ethiop. 2022, 36(2), 339-351.                                                               

DOI: https://dx.doi.org/10.4314/bcse.v36i2.8