Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015

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

Authors
Li Bi, Ruijuan Zhang
Corresponding Author
Li Bi
Available Online December 2015.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
Part of series
Advances in Computer Science Research
Publication Date
December 2015
ISBN
978-94-6252-133-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmmcce-15.2015.211How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.211
DO  - https://doi.org/10.2991/icmmcce-15.2015.211
ID  - Bi2015/12
ER  -