Optimizing CNC machining processes is critical for improving performance and efficiency. Energy consumption during the cutting process is an important optimization target, as researchers and manufacturers want to lower operational costs by using as little energy as possible in CNC machining. This study addresses the problem of lowering energy usage in goods cut with a Hartford 5A-25R 5-Axis CNC machine. Five parameters, each with three levels, were investigated: spindle speed, feed rate, depth of cut, width of cut, and coolant mode. A Taguchi Orthogonal array L27 Design of Experiment was used to optimize process. The optimal combination of cutting parameters for minimizing energy consumption involves using a wide width of cut, dry cutting mode, high spindle speed, high feed rate, and a large depth of cut. The study revealed that width of cut and coolant mode are the two most influential parameters among the cutting parameters. These two parameters significantly affect the performance of the responses.

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Energy Consumption Optimization on Aluminum 6061 Curve Cutting Using 5-Axis CNC Machine

  • Najmuddin Yahya,
  • Hariyanto Gunawan,
  • Muhammad Akbar

摘要

Optimizing CNC machining processes is critical for improving performance and efficiency. Energy consumption during the cutting process is an important optimization target, as researchers and manufacturers want to lower operational costs by using as little energy as possible in CNC machining. This study addresses the problem of lowering energy usage in goods cut with a Hartford 5A-25R 5-Axis CNC machine. Five parameters, each with three levels, were investigated: spindle speed, feed rate, depth of cut, width of cut, and coolant mode. A Taguchi Orthogonal array L27 Design of Experiment was used to optimize process. The optimal combination of cutting parameters for minimizing energy consumption involves using a wide width of cut, dry cutting mode, high spindle speed, high feed rate, and a large depth of cut. The study revealed that width of cut and coolant mode are the two most influential parameters among the cutting parameters. These two parameters significantly affect the performance of the responses.