NATURE-INSPIRED METAHEURISTIC ALGORITHMS IN OPTIMIZATION OF MACHINING PARAMETERS

Abstract

Improving productivity, quality, and efficiency in manufacturing relies heavily on the precise selection of machining parameters. These parameters, such as cutting speed, feed, depth of cut, and tool selection, play a crucial role in achieving optimal results. The optimization of these parameters not only has the potential to reduce costs and minimize waste but also contributes to enhancing product consistency. This paper uses the experimental results from a practical setting and proposes the application of nature-inspired metaheuristics to optimize machining parameters. The main objective is to minimize cutting forces while optimizing the parameters involved in a turning process. The study compares and briefly discusses the optimization results obtained through three nature-inspired metaheuristic algorithms.