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A hybrid neural network and selective allowance approach for internal due date assignment in a wafer fabrication plant

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Abstract

A hybrid neural network and selective allowance approach is proposed in this study for internal due date assignment in a wafer fabrication plant (wafer fab). In the first part, a look-ahead self-organization map-fuzzy back propagation network (SOM-FBPN) is constructed to estimate the completion time of a job. Subsequently, a selective allowance policy is established to determine the allowance that will be added to the estimated job completion time. Compared with traditional approaches, the look-ahead SOM-FBPN has many features (including incorporating the future release plan, classifying jobs, and incorporating expert opinions), and the selective allowance policy is novel by considering two different production control issues to avoid missing the due date. According to experimental results, the prediction accuracy of the look-ahead SOM-FBPN was significantly better than those of many existing approaches. Besides, the selective allowance policy considerably improved the due date related performance after adding some extra allowance.

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Authors and Affiliations

  1. Department of Industrial Engineering and Systems Management, Feng Chia University, No. 100, Wenhwa Rd., Seatwen, Taichung City, Taiwan

    Toly Chen, Angus Jeang & Yi-Chi Wang

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  1. Toly Chen
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  2. Angus Jeang
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  3. Yi-Chi Wang
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Correspondence to Toly Chen.

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Chen, T., Jeang, A. & Wang, YC. A hybrid neural network and selective allowance approach for internal due date assignment in a wafer fabrication plant. Int J Adv Manuf Technol 36, 570–581 (2008). https://doi.org/10.1007/s00170-006-0869-8

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  • DOI: https://doi.org/10.1007/s00170-006-0869-8

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