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Estimating the simulation workload for factory simulation as a cloud service

Author

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  • Toly Chen

    (Feng Chia University)

  • Chi-Wei Lin

    (Feng Chia University)

Abstract

An essential and practical application of cloud manufacturing is factory simulation as a cloud service (FSaaCS). In this paper, several topics related to implementing FSaaCS are discussed. Among them, load balancing is considered a critical topic. To address this topic, estimating a simulation workload is a crucial step. After factors critical to estimating a simulation workload were summarized, several methods were applied to estimate a simulation load, relevant to the required simulation time, from these factors. An experiment using real data was conducted to compare the performance of these methods. In addition, the paired $$t$$ t test was performed and the results indicated that the performance of the fuzzy collaborative method is superior to those of some existing methods.

Suggested Citation

  • Toly Chen & Chi-Wei Lin, 2017. "Estimating the simulation workload for factory simulation as a cloud service," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1139-1157, June.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:5:d:10.1007_s10845-015-1068-y
    DOI: 10.1007/s10845-015-1068-y
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    References listed on IDEAS

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    1. Christoph Zott, 2003. "Dynamic capabilities and the emergence of intraindustry differential firm performance: insights from a simulation study," Strategic Management Journal, Wiley Blackwell, vol. 24(2), pages 97-125, February.
    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.
    3. Eliezer Dekel & Sartaj Sahni, 1983. "Parallel Scheduling Algorithms," Operations Research, INFORMS, vol. 31(1), pages 24-49, February.
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