A hybrid intelligent approach for output projection in a semiconductor fabrication plant

Article type: Research Article

Authors: Chen, Toly^{; *} | Wang, Yi-Chi

Affiliations: Department of Industrial Engineering and Systems Management, Feng Chia University, Taichung, Taiwan 407

Correspondence: [*] Corresponding author. E-mail: tolychen@ms37.hinet.net.

Abstract: 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.

Keywords: Fuzzy neural network, fuzzy c-means, fuzzy back propagation neural network, output projection, semiconductor fabrication

DOI: 10.3233/IDA-2008-12108

Journal: Intelligent Data Analysis, vol. 12, no. 1, pp. 129-144, 2008