Abrasive waterjet machining of titanium alloy using an integrated approach of taguchi-based passing vehicle search algorithm

Abstract The titanium alloy, Ti6Al4V, is a popularly used material in aerospace and medical applications due to its specific attributes, such as excellent strength-to-weight ratio and resistance to corrosion. Ti6Al4V is challenging to machine using conventional methods due to its poor thermal conductivity, which necessitates the use of unconventional machining methods like abrasive water jet machining (AWJM). In this work, AWJM was preferred for machining Ti6Al4V, considering three key process variables: nozzle traverse speed (T v ), abrasive flow rate (A f ), and stand-off distance (S d ). The performance of the AWJM process was assessed using three main metrics: Material removal rate (MRR), Surface roughness (SR), and Kerf taper angle (θ), which were crucial for evaluating the effectiveness of the AWJM. Taguchi’s L9 array, a design of experiments method, was used to plan the experiments. The adequacy of the developed models was assessed by analysis of variance (ANOVA). ANOVA results have shown that T v , A f , and S d were found to have a significant effect on MRR, SR, θ with contributions of 73.15%, 49.72%, and 78.35% respectively. The Passing Vehicle Search algorithm was adopted to find the global optimal solution. Simultaneous optimization results using the PVS algorithm have shown the optimal MRR, SR, and θ values of 0.17 g/min, 3.28 μm, and 2.45, respectively, at T v of 237 mm/min, A f of 450 g/min, and S d of 2.0 mm. The optimization results with Pareto points will help to achieve desired outcomes by selecting appropriate input conditions.