Modeling and optimization of drilling operation of lead-free brass alloys considering various cutting tool geometries and copper content

Abstract

Machinability, stable productivity, and quality of the components are crucial factors in manufacturing industry. In industrial applications, when cutting parameters and conditions are determined considering experiences gained by engineers which does not resolve the whole problems faced with in case cutting tools and their geometries are involved. Thus, it requires further knowledge that is built through systematic and scientific research. This study presents the results of an experimental investigation of a drilling process of hot forged lead-free brass alloys by using a form cutting tool. Experimental data on cutting forces, dimensional accuracy, and surface quality of the holes is presented considering the tools with different geometries, feed rates and rotational speeds on hot forged lead-free brass alloys with various copper content. Artificial neural networks modelling, and genetic algorithm-based optimization methods have been used to predict and optimize the machining process and related responses. The computational results demonstrated that the developed model and optimization procedure can notably improve the efficiency of the process by reducing the production cost with the obtained optimum machining conditions.