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Son, Hungsun
Electromechanical Systems & Control Lab (ESCL)
Research Interests
  • Magnetic field modeling

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Development of prediction model for root industry production process using artificial neural network

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Title
Development of prediction model for root industry production process using artificial neural network
Other Titles
인공신경망을 이용한 뿌리산업 생산공정 예측 모델 개발
Author
Bak, ChanbeomSon, Hungsun
Keywords
Neural network (인공신경망); Root industry (뿌리산업); Casting (주조); Smart factory (스마트팩토리)
Issue Date
201701
Publisher
한국정밀공학회
Citation
JOURNAL OF THE KOREAN SOCIETY FOR PRECISION ENGINEERING, v.34, no.1, pp.23 - 27
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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DOI
http://dx.doi.org/10.7736/KSPE.2017.34.1.23
ISSN
1225-9071
Appears in Collections:
MNE_Journal Papers
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