Abstract
In this paper, we suggest a method that applies RFID tag information and a data mining technology to a manufacturing execution system (MES) for efficient process control. The MES is an efficient process control method for many enterprises. But, the MES is not an analysis technique for process control. Therefore, we will supplement a data mining technology and RFID tag information to generate a more efficient process control system. In order to accomplish this, we designed and implemented an efficient product control system and adapted it to a TFT LCD production line using RFID tag information and data mining. As a result, the method proposed solved defects in parts and problems of personnel expenses.
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References
Manufacturing Execution System - A Concept Node, TATA consultancy services (2002)
Integration of MES with Planning and Scheduling Solutions. Broner Metals Solutions Ltd - Watford, UK (2004)
Tao, Y.-H., Hong, T.-P., Sun, S.-I.: An XML implementation process model for enterprise applications. Computer in Industry 55 (2004)
Farahvash, P., Boucher, T.O.: A multi-agent architecture for control of AGV system. Robotics and computer-Integrated manufacturing 20 (2004)
Rivest, J.R., Szydlo, M.: The Blocker Tag: Selective Blocking of RFID TAG for Consumer Privacy. In: 10th ACM CCS, ACM Press, New York (2003)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)
Abdi, H.: A neural network primer. Journal of Biological Systems 2, 247–281 (1994)
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© 2007 Springer Berlin Heidelberg
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Kim, C., Nam, SY., Park, DJ., Park, I., Hyun, TY. (2007). Product Control System Using RFID Tag Information and Data Mining. In: Stajano, F., Kim, H.J., Chae, JS., Kim, SD. (eds) Ubiquitous Convergence Technology. ICUCT 2006. Lecture Notes in Computer Science, vol 4412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71789-8_11
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DOI: https://doi.org/10.1007/978-3-540-71789-8_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71788-1
Online ISBN: 978-3-540-71789-8
eBook Packages: Computer ScienceComputer Science (R0)