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Information Composition Analysis and Adaptation Access of CNC Lathes in Cloud Manufacturing Environment

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Challenges and Opportunity with Big Data (Monterey Workshop 2016)

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Abstract

Aiming at the complicated information composition and the features such as high-degree autonomous, disperse, dynamic and changeable, and adaptive function of CNC lathes in cloud manufacturing environment, a framework for Adaptation Access of CNC lathes is proposed, which could support various types of information modular, dynamic virtual access. The key technologies such as service modeling approach of CNC lathes based on Web Service Modeling Ontology (WSMO) and Adaptation Access of CNC lathes based on Open Service Gateway Initiative (OSGI) are researched. Finally, an experimental case is used to verify the above research results.

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Acknowledgment

This work was supported by the National High-Tech. R&D Program, China (No. 2015AA042102), and the Science and Technology Program of Guangdong Province (No. 2015A010103022).

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Authors and Affiliations

  1. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China

    Lei Qiu & Chao Yin

  2. School of Economics and Business Administration, Chongqing University, Chongqing, China

    Xiao-bin Li

Authors
  1. Lei Qiu
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  2. Chao Yin
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  3. Xiao-bin Li
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Corresponding author

Correspondence to Xiao-bin Li .

Editor information

Editors and Affiliations

  1. Beihang University, Beijing, China

    Lin Zhang

  2. Beihang University, Beijing, China

    Lei Ren

  3. Université Pierre and Marie Curie, Paris, France

    Fabrice Kordon

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Qiu, L., Yin, C., Li, Xb. (2017). Information Composition Analysis and Adaptation Access of CNC Lathes in Cloud Manufacturing Environment. In: Zhang, L., Ren, L., Kordon, F. (eds) Challenges and Opportunity with Big Data. Monterey Workshop 2016. Lecture Notes in Computer Science(), vol 10228. Springer, Cham. https://doi.org/10.1007/978-3-319-61994-1_7

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  • DOI: https://doi.org/10.1007/978-3-319-61994-1_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61993-4

  • Online ISBN: 978-3-319-61994-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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