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CAO Zhengcai, ZHAO Huidan, WANG Yongji. ANFIS and SA Based Approach to Prediction, Scheduling, and Performance Evaluation for Semiconductor Wafer Fabrication[J]. Chinese Journal of Electronics, 2013, 22(1): 25-30.
Citation: CAO Zhengcai, ZHAO Huidan, WANG Yongji. ANFIS and SA Based Approach to Prediction, Scheduling, and Performance Evaluation for Semiconductor Wafer Fabrication[J]. Chinese Journal of Electronics, 2013, 22(1): 25-30.
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ANFIS and SA Based Approach to Prediction, Scheduling, and Performance Evaluation for Semiconductor Wafer Fabrication

  • 1.

    College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China;

  • 2.

    State Key Laboratory of Manufacturing Systems Engineering, Xi’an Jiaotong University Xi’an 710054, China;

  • 3.

    State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China

Funds: This work is supported by the New Scholars Program of Doctoral Fund of Ministry of Education (No.20090010120011), the Open Project Program of the State Key of CAD&CG (No.A1120); the Open Project Program of the State Key Lab of Industrial Control Technology (No.ICT1108) and the Foundation of Key Laboratory of System Control and Information Processing, Ministry of Education of China (No.SCIP2011005).
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  • Received Date: October 31, 2011
  • Revised Date: December 31, 2011
  • Published Date: January 04, 2013
    Graphical Abstract
    • Abstract
  • In this paper, an optimized mechanism for Semiconductor wafer fabrication (SWF) by integrating the Adaptive neuro-fuzzy inference system (ANFIS) with Simulated annealing (SA) algorithm is proposed. In this approach, aiming to solve the rush order problem which significantly affect the cycle time and impact the Work in process (WIP) of lots due to the high priority, we build an ANFIS based prediction model which will be embedded into releasing to forecast product codes and quantities of the contingent rush orders. Then a scheduler based on SA algorithm is constructed, the coding of which represents a combination of scheduling policies, including lot releasing policies, dispatching rules, batching rules and settingup rules. When the SA finished its optimization process, an optimal scheduling policy is produced. By using the proposed approach??we will find that the system can be optimized to a large extent and give a better performance.
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    • References (11)
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