A model for machining with nano-additives based minimum quantity lubrication

Abstract

The high temperature generated when machining aerospace alloys namely, titanium and nickel alloys, accelerate the tool wear rate and affects the physical properties of the machined surface. Flood coolant is usually the effective traditional solution to dissipate the heat and reduce its negative impact on tool performance and surface integrity. The disposal of the coolant causes environmental concerns, and the generated fumes during machining also present health concerns. Minimum quantity lubricant is presented as an alternative coolant strategy to reduce the amount of used coolant and environmental concerns associated with flood coolant. Experimental investigations showed that MQL does not offer the same results obtained when using flood coolant during machining titanium and Inconel. However, the addition of nano-additives significantly improved the performance of MQL. In this work, an integrated model (i.e., finite element and finite volume) is developed to analyze various unique aspects of machining with nano-fluids under minimum quantity lubrication during cutting Inconel 718 and Ti-6Al-4V alloys. These aspects include the heat transfer characteristics of the resultant nano-cutting fluid, the interactions between the cutting tool and workpiece, the generated cutting temperature at different zones, and resulting residual stresses. The investigation was carried out through two main phases. A 2-D axisymmetric computational fluid dynamics (CFD) model is developed to simulate the thermal effect of resultant nano-mist and obtain the thermal characteristics of the nano-fluid. The obtained results are then used in the finite element model to simulate the machining process with nano-fluid. The average heat convection coefficients results provided from the proposed CFD model at standard room temperature demonstrated a good agreement with the theoretical values calculated throughout this work. Also, the simulated and experimental cutting forces showed better agreement in the case of cutting test performed without nano-additives (accuracy % ≈ 90%) than the cutting test performed with nano-additives (accuracy % ≈ 82.3%). This work presents a first attempt in the open literature to simulate the machining processes using MQL-nano-fluid.