An experimental study on Avocado oil-based TiO 2 cutting fluid for Minimum Quantity Lubrication in milling of AISI 4130 steel

Abstract In machining operation, cutting fluid serves a great role through lubricating and cooling the work-tool interface and cleaning chips from the machining zone. Consequently, the tribological state at the interfaces is affected by a cutting fluid. However, conventional cutting fluids negatively affect the machining environment by excess use and reduced quality. This has given rise to a new kind of cutting fluid with good thermo-physical properties to reduce excessive use in machining. In this work, a cutting fluid is formed by dispersing TiO₂ nanoparticles into avocado oil-immersed water at different concentrations. The prepared cutting fluid is characterized by its thermal conductivity, density, pH value, viscosity, and stability. Moreover, its performance is evaluated in the milling of AISI 4130 steel by preparing the minimum quantity lubrication (MQL) setup. A total of 27 machining experiments were done based on Taguchi’s orthogonal array. The experimental work revealed that the increase in the TiO₂ concentration in the base liquid enhanced its viscosity and thermal conductivity. Average enhancements of 61.98% and 48.2% are obtained in terms of viscosity and thermal conductivity respectively than the previously used cutting fluid. The performance of the optimized parameters by using Taguchi-based Grey Relational Analysis showed improvement of 9.412%, 9.21%, 26.087%, and 6.477% in terms of material removal rate (MRR), surface roughness (Ra), tool wear rate (Vb), and temperature respectively. A 17.2% and 91.48% improvement in Ra, 77.87% and 63.52% in temperature are achieved than the dry and flood conditions respectively. The Analysis of Variance (ANOVA) results showed the selected parameters are significant with the consistent interactions among cutting fluid composition, speed, feed rate, and depth of cut (DOC) for the responses. Correctly chosen composition of cutting fluid and machining parameters with the MQL condition can enhance its properties and improve the machining performances.