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Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 471973, 9 pages
http://dx.doi.org/10.1155/2012/471973
Research Article

A Nonlinear Programming and Artificial Neural Network Approach for Optimizing the Performance of a Job Dispatching Rule in a Wafer Fabrication Factory

Department of Industrial Engineering and Systems Management, Feng Chia University, No. 100 Wenhwa Road, Seatwen, Taichung 407, Taiwan

Received 21 May 2012; Accepted 18 July 2012

Academic Editor: Yi-Chi Wang

Copyright © 2012 Toly Chen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. C. N. Wang and C. H. Wang, “A simulated model for cycle time reduction by acquiring optimal lot size in semiconductor manufacturing,” International Journal of Advanced Manufacturing Technology, vol. 34, no. 9-10, pp. 1008–1015, 2007. View at Publisher · View at Google Scholar · View at Scopus
  2. T. Chen and Y. C. Lin, “A fuzzy-neural fluctuation smoothing rule for scheduling jobs with various priorities in a miconductor manufacturing factory,” International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, vol. 17, no. 3, pp. 397–417, 2009. View at Publisher · View at Google Scholar · View at Scopus
  3. T. Chen and Y. C. Wang, “A nonlinear scheduling rule incorporating fuzzy-neural remaining cycle time estimator for scheduling a semiconductor manufacturing factory-a simulation study,” International Journal of Advanced Manufacturing Technology, vol. 45, no. 1-2, pp. 110–121, 2009. View at Publisher · View at Google Scholar · View at Scopus
  4. T. Chen, “Optimized fuzzy-neuro system for scheduling wafer fabrication,” Journal of Scientific and Industrial Research, vol. 68, no. 8, pp. 680–685, 2009. View at Scopus
  5. D. A. Koonce and S. C. Tsai, “Using data mining to find patterns in genetic algorithm solutions to a job shop schedule,” Computers and Industrial Engineering, vol. 38, no. 3, pp. 361–374, 2000. View at Publisher · View at Google Scholar · View at Scopus
  6. B. W. Hsieh, C. H. Chen, and S. C. Chang, “Scheduling semiconductor wafer fabrication by using ordinal optimization-based simulation,” IEEE Transactions on Robotics and Automation, vol. 17, no. 5, pp. 599–608, 2001. View at Publisher · View at Google Scholar · View at Scopus
  7. H. J. Yoon and W. Shen, “A multiagent-based decision-making system for semiconductor wafer fabrication with hard temporal constraints,” IEEE Transactions on Semiconductor Manufacturing, vol. 21, no. 1, pp. 83–91, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. Y. Harrath, B. Chebel-Morello, and N. Zerhouni, “A genetic algorithm and data mining based meta-heuristic for job shop scheduling problem,” in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp. 280–285, October 2002. View at Scopus
  9. K. Sourirajan and R. Uzsoy, “Hybrid decomposition heuristics for solving large-scale scheduling problems in semiconductor wafer fabrication,” Journal of Scheduling, vol. 10, no. 1, pp. 41–65, 2007. View at Publisher · View at Google Scholar · View at Scopus
  10. S. C. H. Lu, D. Ramaswamy, and P. R. Kumar, “Efficient scheduling policies to reduce mean and variance of cycle-time in semiconductor manufacturing plants,” IEEE Transactions on Semiconductor Manufacturing, vol. 7, no. 3, pp. 374–388, 1994. View at Publisher · View at Google Scholar · View at Scopus
  11. K. Altendorfer, B. Kabelka, and W. Stöcher, “A new dispatching rule for optimizing machine utilization at a semiconductor test field,” in Proceedings of the IEEE/SEMI Advanced Semiconductor Manufacturing Conference (ASMC '07), pp. 188–193, June 2007. View at Publisher · View at Google Scholar · View at Scopus
  12. H. Zhang, Z. Jiang, and C. Guo, “Simulation-based optimization of dispatching rules for semiconductor wafer fabrication system scheduling by the response surface methodology,” International Journal of Advanced Manufacturing Technology, vol. 41, no. 1-2, pp. 110–121, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. T. Chen, “Fuzzy-neural-network-based fluctuation smoothing rule for reducing the cycle times of jobs with various priorities in a wafer fabrication plant: a simulation study,” Proceedings of the Institution of Mechanical Engineers Part B, Journal of Engineering Manufacture, vol. 223, no. 8, pp. 1033–1043, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. T. Chen, “A tailored non-linear fluctuation smoothing rule for semiconductor manufacturing factory scheduling,” Proceedings of the Institution of Mechanical Engineers Part I, Journal of Systems and Control Engineering, vol. 223, no. 2, pp. 149–160, 2009. View at Publisher · View at Google Scholar · View at Scopus
  15. T. Chen, “Intelligent scheduling approaches for a wafer fabrication factory,” Journal of Intelligent Manufacturing, vol. 23, no. 3, pp. 897–911, 2012. View at Publisher · View at Google Scholar · View at Scopus
  16. T. Chen and Y. C. Wang, “A bi-criteria nonlinear fluctuation smoothing rule incorporating the SOM-FBPN remaining cycle time estimator for scheduling a wafer fab—a simulation study,” International Journal of Advanced Manufacturing Technology, vol. 49, no. 5–8, pp. 709–721, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. T. Chen, Y.-C. Wang, and Y.-C. Lin, “A bi-criteria four-factor fluctuation smoothing rule for scheduling jobs in a wafer fabrication factory,” International Journal of Innovative Computing, Information and Control, vol. 6, pp. 4289–4303, 2010.
  18. T. Chen, “Dynamic fuzzy-neural fluctuation smoothing rule for jobs scheduling in a wafer fabrication factory,” Proceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering, vol. 223, no. 8, pp. 1081–1094, 2009. View at Publisher · View at Google Scholar · View at Scopus
  19. T. Chen, “An optimized tailored nonlinear fluctuation smoothing rule for scheduling a semiconductor manufacturing factory,” Computers and Industrial Engineering, vol. 58, no. 2, pp. 317–325, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. T. Chen, Y. C. Wang, and H. C. Wu, “A fuzzy-neural approach for remaining cycle time estimation in a semiconductor manufacturing factory—a simulation study,” International Journal of Innovative Computing, Information and Control, vol. 5, no. 8, pp. 2125–2139, 2009. View at Scopus
  21. Y. C. Wang, T. Chen, and C. W. Lin, “A slack-diversifying nonlinear fluctuation smoothing rule for job dispatching in a wafer fabrication factory,” Robotics & Computer Integrated Manufacturing. In press.
  22. T. Chen and T. Wang, “Enhancing scheduling performance for a wafer fabrication factory: the bi-objective slack-diversifying nonlinear fluctuation-smoothing rule,” Computational Intelligence and Neuroscience. In press.
  23. T. Chen and M. Huang, “A fuzzy-neural slack-diversifying NFS rule for job dispatching in a wafer fabrication factory,” ICIC Express Letters, vol. 6, no. 9, pp. 2243–2248, 2012.
  24. X. L. Xie and G. Beni, “A validity measure for fuzzy clustering,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 8, pp. 841–847, 1991. View at Publisher · View at Google Scholar · View at Scopus
  25. T. Chen and Y. C. Lin, “A fuzzy back propagation network ensemble with example classification for lot output time prediction in a wafer fab,” Applied Soft Computing Journal, vol. 9, no. 2, pp. 658–666, 2009. View at Publisher · View at Google Scholar · View at Scopus
  26. T. Chen, Y. C. Wang, and H. R. Tsai, “Lot cycle time prediction in a ramping-up semiconductor manufacturing factory with a SOM-FBPN-ensemble approach with multiple buckets and partial normalization,” International Journal of Advanced Manufacturing Technology, vol. 42, no. 11-12, pp. 1206–1216, 2009. View at Publisher · View at Google Scholar · View at Scopus
  27. T. Nakata, K. Matsui, Y. Miyake, and K. Nishioka, “Dynamic bottleneck control in wide variety production factory,” IEEE Transactions on Semiconductor Manufacturing, vol. 12, no. 3, pp. 273–280, 1999. View at Publisher · View at Google Scholar · View at Scopus
  28. T. Chen, “Job cycle time estimation in a wafer fabrication factory with a bi-directional classifying fuzzy-neural approach,” International Journal of Advanced Manufacturing Technology, vol. 56, pp. 1007–1018, 2011. View at Publisher · View at Google Scholar · View at Scopus