Research on yield forecasting model based on RBF in discrete manufacturing industry application

DOI

10.2991/icmmcce-15.2015.211How to use a DOI?

Keywords

Neural Networks; Advanced Planning and Scheduling prediction model Forecast period

Abstract

Yield forecasting system in discrete manufacturing is a dynamic complex systems with a number of factors, face such a complex and large system is difficult to directly general system to the enterprise, therefore need to give a company's production forecast model. On the background of Wuzhong Instrument company application, this paper by RBF(radical basis function) neural networks and generalized regression neural network algorithm were compared in enterprise applications, to find the most suitable production forecast model in Wuzhong Instrument company, then Analysis and comparison shows the experimental results . The model has been applied to the valve, spool and valve seat yield prediction in the advanced planning and scheduling in which the practical arrangements played a major role for production planning of Wuzhong Instrument company.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Li Bi
AU  - Ruijuan Zhang
PY  - 2015/12
DA  - 2015/12
TI  - Research on yield forecasting model based on RBF in discrete manufacturing industry application
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SP  - 933
EP  - 938
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.211
DO  - 10.2991/icmmcce-15.2015.211
ID  - Bi2015/12
ER  -