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A new cloud computing method for establishing asymmetric cycle time intervals in a wafer fabrication factory

Author

Listed:
  • Toly Chen

    (Feng Chia University)

  • Hsin-Chieh Wu

    (Chaoyang University of Technology)

Abstract

Estimating the cycle time of each job in a wafer fabrication factory is critical. An equally critical problem is to estimate the range of a cycle time. This topic has rarely been discussed because most existing methods for range calculation establish only a symmetric range. However, a symmetric range does not meet the requirements of managerial applications based on the lower and upper bounds of a cycle time. Recently, a few researchers have attempted to establish the asymmetric bounds of a cycle time. However, these methods either have overly complex computations or do not consistently perform well. This study proposes a new approach for effective cycle-time bounding. First, construction of a back propagation network predicts the cycle time of a job. Second, two linear functions of the output are formed, and the threshold on the output node is fuzzified to derive the lower and upper bounds of the cycle time. In theory, such a treatment tightens the lower and upper bounds and improves the forecasting precision. Third, theorems for the feasibility of the two linear functions are proved. Fourth, a cloud computing scheme is proposed to improve the bounds in an effective manner. Finally, a real case illustrates the applicability of the proposed methodology. Experimental results show that this methodology narrows the range of cycle times for untrained data by 31 %, while maintaining a considerably high hit rate of 92.5 %.

Suggested Citation

  • Toly Chen & Hsin-Chieh Wu, 2017. "A new cloud computing method for establishing asymmetric cycle time intervals in a wafer fabrication factory," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1095-1107, June.
  • Handle: RePEc:spr:joinma:v:28:y:2017:i:5:d:10.1007_s10845-015-1052-6
    DOI: 10.1007/s10845-015-1052-6
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    References listed on IDEAS

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    1. O.A. Joseph & R. Sridharan, 2011. "Simulation-based metamodels for the analysis of dynamic due-date assignment in a flexible manufacturing system," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 3(4), pages 341-367.
    2. Toly Chen, 2013. "A Systematic Cycle Time Reduction Procedure for Enhancing the Competitiveness and Sustainability of a Semiconductor Manufacturer," Sustainability, MDPI, vol. 5(11), pages 1-16, November.
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    Cited by:

    1. Xiaobao Zhu & Jing Shi & Fengjie Xie & Rouqi Song, 2020. "Pricing strategy and system performance in a cloud-based manufacturing system built on blockchain technology," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1985-2002, December.
    2. Shiyong Yin & Jinsong Bao & Jie Zhang & Jie Li & Junliang Wang & Xiaodi Huang, 2020. "Real-time task processing for spinning cyber-physical production systems based on edge computing," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 2069-2087, December.
    3. Yu-Cheng Wang & Horng-Ren Tsai & Toly Chen, 2021. "A Selectively Fuzzified Back Propagation Network Approach for Precisely Estimating the Cycle Time Range in Wafer Fabrication," Mathematics, MDPI, vol. 9(12), pages 1-18, June.

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