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Cloud computing-based jam management for a manufacturing system in a Green IT environment

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Abstract

A manufacturing system is composed of and operated by many components; motors, cylinders, and sensors. Its purpose is to increase operational performance without system error or jam. And, recently, the Green IT/S (information technologies and systems) refer to processes that directly or indirectly address environmental sustainability in organizations. Green IT addresses energy consumption, reduces the bad productivity, and increases system operational efficiency using the computer. However, when the system experiences some problem or operational error, users (system operators or managers) often find it difficult to locate the jam position immediately and precisely. It is also difficult to know the cause of the jam and to manage jam information even after they read and find relevant error text in a repair manual for the system. This research proposes a method to efficiently manage jam status for manufacturing systems. For this purpose, a topic map was used. The topic model has topic types, associations, and occurrences, which relate to operational jam, system jam, and system components. All jam status information to support users is managed by XML specification, distinctly and efficiently.

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Acknowledgements

This research supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (NIPA-2013-H0301-13-4007) supervised by the NIPA (National IT Industry Promotion Agency)

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea

    Jong Hyuk Park

  2. Humanitas College, Kyung Hee University, 1 Hoegi-dong, Dongdaemun-gu, Seoul, 130-701, Republic of Korea

    Hwa Young Jeong

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  1. Jong Hyuk Park
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Correspondence to Hwa Young Jeong.

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Park, J.H., Jeong, H.Y. Cloud computing-based jam management for a manufacturing system in a Green IT environment. J Supercomput 69, 1054–1067 (2014). https://doi.org/10.1007/s11227-013-1007-7

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  • DOI: https://doi.org/10.1007/s11227-013-1007-7

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