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A multi-granularity approach for estimating the sustainability of a factory simulation model: semiconductor packaging as an example

Author

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  • Toly Chen

    (National Chiao Tung University)

  • Li-Chih Wang

    (Tunghai University)

  • Min-Chi Chiu

    (National Chin-Yi University of Technology)

Abstract

Dynamic factory simulation has been considered as an effective means to control a factory. However, the large amount of money, time, efforts, and know-how required for conducting a factory simulation study force a factory to pursue the persistent application of the factory simulation model, i.e. the sustainability of the factory simulation model. Therefore, strategies are required to facilitate the rapid establishment of the factory simulation model, to lower the technical requirements of the model, and to reduce the effort and time spent on simulation tasks, thus increasing users’ willingness to continue the application of the model. However, such issues have rarely been discussed. In addition, no method is available for estimating the sustainability of a factory simulation model. To address this problem, short-time evidence was analyzed rather than observing data over a long period. Then, a multi-granularity approach is proposed to estimate the sustainability of a factory simulation model based on these evidences. The proposed methodology has been applied to the simulation of a real semiconductor packaging facility. According to the experimental results, the multi-granularity approach reduced the input space by 89% and maintained a very high estimation accuracy. In addition, it also saved considerable time in building the models for estimating sustainability. Furthermore, without the multi-granularity approach, the sustainability of the factory simulation model could be observed only after a long period.

Suggested Citation

  • Toly Chen & Li-Chih Wang & Min-Chi Chiu, 2018. "A multi-granularity approach for estimating the sustainability of a factory simulation model: semiconductor packaging as an example," Operational Research, Springer, vol. 18(3), pages 711-729, October.
    • Handle: RePEc:spr:operea:v:18:y:2018:i:3:d:10.1007_s12351-017-0342-5
    DOI: 10.1007/s12351-017-0342-5
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    References listed on IDEAS

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    1. Xiong, Hegen & Fan, Huali & Jiang, Guozhang & Li, Gongfa, 2017. "A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints," European Journal of Operational Research, Elsevier, vol. 257(1), pages 13-24.
    2. Toly Chen, 2014. "Strengthening the Competitiveness and Sustainability of a Semiconductor Manufacturer with Cloud Manufacturing," Sustainability, MDPI, vol. 6(1), pages 1-16, January.
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    Cited by:

    1. Hsin-Chieh Wu & Horng-Ren Tsai & Tin-Chih Toly Chen & Keng-Wei Hsu, 2021. "Energy-Efficient Production Planning Using a Two-Stage Fuzzy Approach," Mathematics, MDPI, vol. 9(10), pages 1-17, May.

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