TY - JOUR
T1 - A hybrid intelligent approach for output projection in a semiconductor fabrication plant
AU - Chen, Tin-Chih
AU - Wang, Yi Chi
PY - 2008/9/22
Y1 - 2008/9/22
N2 - A hybrid intelligent approach is proposed which can be used to estimate the output of each product type in a semiconductor fabrication plant. This is a critical task for plant operation. First, the hybrid fuzzy-c-means (FCM) and fuzzy-back-propagation-neural-network (FBPN) approach is applied to estimate the output time for every job in the plant. Subsequently, the fuzzy output projection function (FOPF) is proposed to project the outputs into each future time period. To evaluate the advantages and/or disadvantages of the hybrid intelligent approach, a simulated semiconductor plant model is also used in this study to generate test data. From the experimental results, the output projection accuracy by the hybrid intelligent approach was significantly better than that of some existing approaches.
AB - A hybrid intelligent approach is proposed which can be used to estimate the output of each product type in a semiconductor fabrication plant. This is a critical task for plant operation. First, the hybrid fuzzy-c-means (FCM) and fuzzy-back-propagation-neural-network (FBPN) approach is applied to estimate the output time for every job in the plant. Subsequently, the fuzzy output projection function (FOPF) is proposed to project the outputs into each future time period. To evaluate the advantages and/or disadvantages of the hybrid intelligent approach, a simulated semiconductor plant model is also used in this study to generate test data. From the experimental results, the output projection accuracy by the hybrid intelligent approach was significantly better than that of some existing approaches.
KW - Fuzzy back propagation neural network
KW - Fuzzy c-means
KW - Fuzzy neural network
KW - Output projection
KW - Semiconductor fabrication
UR - http://www.scopus.com/inward/record.url?scp=51849118926&partnerID=8YFLogxK
U2 - 10.3233/IDA-2008-12108
DO - 10.3233/IDA-2008-12108
M3 - Article
AN - SCOPUS:51849118926
VL - 12
SP - 129
EP - 144
JO - Intelligent Data Analysis
JF - Intelligent Data Analysis
SN - 1088-467X
IS - 1
ER -