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An Efficient and Effective Fuzzy Collaborative Intelligence Approach for Cycle Time Estimation in Wafer Fabrication
Author(s) -
Chen Toly
Publication year - 2015
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21721
Subject(s) - wafer fabrication , fuzzy logic , computer science , interval (graph theory) , factory (object oriented programming) , data mining , task (project management) , artificial intelligence , machine learning , industrial engineering , wafer , engineering , mathematics , systems engineering , combinatorics , electrical engineering , programming language
A common characteristic of fuzzy collaborative forecasting methods is the establishment of an interval estimate that is guaranteed to include the actual value. Such a characteristic is crucial to various planning purposes because it reduces the risk of incorrect forecasting. A new fuzzy collaborative forecasting method is proposed in this study to estimate the cycle time of a job in a wafer fabrication factory; this is a critical task for managing the fabrication of wafers. The proposed fuzzy collaborative forecasting method uses a fuzzy back propagation network that effectively improves the precision of estimation. The accuracy is enhanced through expert collaboration. The performance of the proposed methodology was selectively compared with those of two existing fuzzy collaborative forecasting methods by applying them to a real case. The results confirmed that the proposed methodology substantially enhanced the performance in estimating the cycle time of a job.