<![CDATA[CNC Milling Machine is a machine tool that has a large population but low energy efficiency. The machine tool industry consumes about 10% of the national energy, making it the second largest energy user after transportation sector. To obtain efficient machine performance, the motion in the machining process must be controlled by setting the proper machining parameters. However, there is a contradiction in that CAD/CAM operators and programmers often do not understand the impact of such parameter settings and thus determine parameter values arbitrarily. This study aims to optimize machining parameter settings by providing parameter values proven to have energy-friendly performance. The method used in this research is regression-based response surface methodology. Based on numerical simulations and experiments conducted, variations in feed rate and depth of cut were shown to impact energy consumption significantly. Experiments and tests reduced the energy consumption value below 5A for 78% of the total process.]]>
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