Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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Development of Prediction Model for Root Industry Production Process Using Artificial Neural Network

인공신경망을 이용한 뿌리산업 생산공정 예측 모델 개발

  • 박찬범 (울산과학기술원 기계공학과) ;
  • 손흥선 (울산과학기술원 기계공학과)
  • Received : 2016.10.14
  • Accepted : 2016.12.20
  • Published : 2017.01.01
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Abstract

This paper aims to develop a prediction model for the product quality of a casting process. Prediction of the product quality utilizes an artificial neural network (ANN) in order to renovate the manufacturing technology of the root industry. Various aspects of the research on the prediction algorithm for the casting process using an ANN have been investigated. First, the key process parameters have been selected by means of a statistics analysis of the process data. Then, the optimal number of the layers and neurons in the ANN structure is established. Next, feed-forward back propagation and the Levenberg-Marquardt algorithm are selected to be used for training. Simulation of the predicted product quality shows that the prediction is accurate. Finally, the proposed method shows that use of the ANN can be an effective tool for predicting the results of the casting process.

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References

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