Multi-Objective Process Parameter Optimization for Abrasive Air Jet Machining Using Artificial Bee Colony Algorithm

Abrasive air jet machining is a burgeoning non-traditional machining technology particularly suitable for machining brittle non-metallic materials and metals with high hardness. It is very challenging to select the optimal process parameters to achieve desirable machining performance metrics, such as maximizing material removal rate and minimizing machining width while controlling machining depth. In this study, we aimed to achieve multi-objective process parameter optimization for abrasive air jet machining of silicon based on the artificial bee colony algorithm. A series of experiments was carried out to investigate the effect of process parameters, including air pressure, standoff distance, and nozzle traverse speed, on material removal rate, machining width, and machining depth. Mathematical models for machining performance metrics were developed by regression analysis, and a multi-objective optimization model was further formulated. The artificial bee colony algorithm was proposed to solve the optimization problem, and a set of Pareto-optimal solutions was found. The results indicate that the artificial bee colony algorithm is an effective method for multi-objective process parameter optimization in abrasive air jet machining.