Journal of the Korean Society of Manufacturing Technology Engineers (한국생산제조학회지)

The Korean Society of Manufacturing Technology Engineers (한국생산제조학회)
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Improvement of Cutting Conditions in End-milling Using Deep-layered Neural Networks

심층 신경회로망을 이용한 엔드밀 가공의 절삭 조건 개선

  • Lee, Sin-Young (Dept. of Mechanical Engineering, Kunsan National University)
  • Received : 2017.04.26
  • Accepted : 2017.08.09
  • Published : 2017.08.15
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Abstract

Selection of optimal cutting conditions is important for improving productivity and implementing efficient process control in metal machining. In this study, improvement of cutting conditions in machining using end-mills is studied by using deep-layered neural networks, which comprise an input layer, output layer, and two hidden layers. System networks are designed with inputs as cutting conditions, and they output the cutting force. A pseudo-inverse network is designed that has the adjustable cutting condition as output and cutting force and other cutting conditions as input. The combination of the system network and pseudo-inverse network enables selection or improvement of cutting conditions that results in the expected cutting force.

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References

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