The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of COMPUTERS
Transactions ID Number: 20-227
Full Name: Ruey shun Chen
Position: Professor
Age: ON
Sex: Male
Address: no 26, pao san rd, hsinchu Taiwan
Country: TAIWAN
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E-mail address: rschen@cute.edu.tw
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Title of the Paper: Using Data Mining Technology to Design an Intelligence Control System in Manufacture Industry
Authors as they appear in the Paper: R. S. Chen, Y. C. Chen and C.C. Chen*
Email addresses of all the authors:
Number of paper pages: 8
Abstract: Data mining technology is another powerful tool for manufacturing industries to discovery useful information. In the manufacturing industries, data mining system could be integrated with CIM system in order to analyze the data of the real situation of the manufacturing process. This paper proposed a method and prototype system architecture, which integrated data mining technology and process control with CIM system. We selected ant colony optimization and decision tree as the data mining, and used statistical process control and advanced process control as process control mechanism. The result of this paper shows that the process yield rate can be improved, through the use of automatic and optimum parameter manufacturing. The proposed method and system architecture can be applied in the process analysis of traditional manufacturing industry to discover the main inconsistency reasons in the manufacturing process and compare to classification analysis of the two me!
thods, so as to set up an intelligence control system providing an efficiency tool for analyzing problems, with a view to identifying the causes of problems, making decision immediately, and eventually reducing the cycle time taken to solve quality-related problems. The contributions of this paper are as follows. Predictions made by decision tree analysis, indicating that decision tree analysis is an effective mean of classification analysis in semiconductor quality problems, whereas evaluation of feasible methods by data mining followed by establishment of the basis for a quality analysis system environment, that is characteristic of knowledge sharing may be applied to analysis of the quality problems in all corporation
Keywords: Data mining, Intelligence control systems , Manufacture industry, Olap, Decision tree.
EXTENSION of the file: .pdf
Special (Invited) Session: Using Data Mining Technology to Deign an Quality Control System for Manufacturing Industry
Organizer of the Session: ID: 104-260
How Did you learn about congress: mychen@ntit.edu.tw ; dvd000001@gmail.com ; chen1868@gmail.com ; pc3688tw@gmail.com
IP ADDRESS: 123.195.29.33
