Journal of the Korean Society of Manufacturing Process Engineers (한국기계가공학회지)

The Korean Society of Manufacturing Process Engineers (한국기계가공학회)
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A Study on the Application of ANN for Surface Roughness Prediction in Side Milling AL6061-T4 by Endmill

AL6061-T4의 측면 엔드밀 가공에서 표면거칠기 예측을 위한 인공신경망 적용에 관한 연구

  • Chun, Se-Ho (Department of Mechanical Engineering, Keimyung College University)
  • 천세호 (계명문화대학교 기계과)
  • Received : 2021.03.02
  • Accepted : 2021.03.29
  • Published : 2021.05.31
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Abstract

We applied an artificial neural network (ANN) and evaluated surface roughness prediction in lateral milling using an endmill. The selected workpiece was AL6061-T4 to obtain data of surface roughness measurement based on the spindle speed, feed, and depth of cut. The Bayesian optimization algorithm was applied to the number of nodes and the learning rate of each hidden layer to optimize the neural network. Experimental results show that the neural network applied to optimize using the Expected Improvement(EI) algorithm showed the best performance. Additionally, the predicted values do not exactly match during the neural network evaluation; however, the predicted tendency does march. Moreover, it is found that the neural network can be used to predict the surface roughness in the milling of aluminum alloy.

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References

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