Energy-Efficient Process Parameter Optimization in Multi-Axis CNC Milling Using Genetic Algorithms

Abstract

This paper explores the integration of genetic algorithms (GAs) into multi-axis CNC milling operations to optimize machining parameters for minimal energy consumption while maintaining high-quality output. It discusses how energy aware optimization contributes to sustainable manufacturing and outlines the use of evolutionary algorithms in achieving this dual goal. The research emphasizes the balance between productivity and environmental responsibility, highlighting computational efficiency and real-world applicability. Experimental validation and simulations are presented to demonstrate energy savings without degrading surface quality or tool life.

Keywords: Genetic Algorithms, Energy Efficiency, CNC Milling, Process Optimization, Sustainable Manufacturing