A machine learning approach for simulation of multi-stage laser forming process
Author:
Affiliation:
1. Graduate School of Advanced Science and Engineering, Hiroshima University
2. YASDA PRECISION TOOLS K.K.
3. Department of Mechanical Engineering, National Institute of Technology, Fukui College
Publisher
Japan Society of Mechanical Engineers
Subject
Industrial and Manufacturing Engineering,Mechanical Engineering
Link
https://www.jstage.jst.go.jp/article/jamdsm/17/1/17_2023jamdsm0006/_pdf
Reference42 articles.
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2. Dearden, G., Edwardson, S.P., Abed, E., Bartkowiak, K. and Watkins, K.G., Correction of Distortion and Design Shape in Aluminum Structures Using Laser Forming, ICALEO 2006 (2006), pp.505, DOI:10.2351/1.5060920.
3. De Wilde, P., Lecture Notes in Control and Information Sciences Vol.210 Neural Network Models - An Analysis - (1995), Springer, London.
4. Gatea, S., Ou, H. and McCartney, G., Review on the Influence of Process Parameters in Incremental Sheet Forming, The International Journal of Advanced Manufacturing Technology, Vol. 87 (2016), pp. 479-499, DOI: 10.1007/s00170-016-8426-6.
5. Geiger, M., Synergy of Laser Material Processing and Metal Forming, CIRP Annals, Vol. 43, No.2 (1994), pp. 563-570, DOI: 10.1016/S0007-8506(07)60502-2.
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