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Manufacturing Service Reconfiguration Optimization Using Hybrid Bees Algorithm in Cloud Manufacturing

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Challenges and Opportunity with Big Data (Monterey Workshop 2016)

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Abstract

During the execution process of a cloud manufacturing (CMfg) system, manufacturing service may become faulty to cause the violation of whole production processes against the predefined constraints. It is necessary to timely adjust service aggregation process to the runtime failure during manufacturing process. Therefore it is significant to do service reconfiguration to enhance the reliability of service-oriented manufacturing applications. The issues of the runtime service process reconfiguration based on QoS and energy consumption have been studied. In this paper, by contrast, an effective reconfiguration strategy is proposed to identify reconfiguration regions rather than the whole service process. Moreover, a hybrid bees algorithm (HBA) combining discrete bees algorithm (DBA) with discrete particle swarm optimization (DPSO) is developed to explore the replaceable services during service reconfiguration process. The experiment results show that most of manufacturing service aggregation processes can be repaired by replacing only a small number of services, and HBA is more efficient when finding the replaceable manufacturing services set compared with the existing algorithms.

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Acknowledgments

This research is supported by National Natural Science Foundation of China (Grant No. 51305319), the National High Technology Research and Development Program of China (863 Program) (Grant No. 2015AA042101), and the Fundamental Research Funds for the Central Universities (Grant No. 2015III003).

Author information

Authors and Affiliations

  1. School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, China

    Wenjun Xu, Xin Zhong, Yuanyuan Zhao & Zude Zhou

  2. Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan, 430070, China

    Wenjun Xu, Xin Zhong, Yuanyuan Zhao & Zude Zhou

  3. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    Lin Zhang

  4. Department of Mechanical Engineering, School of Engineering, University of Birmingham, Birmingham, B15 2TT, UK

    Duc Truong Pham

Authors
  1. Wenjun Xu
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  2. Xin Zhong
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  3. Yuanyuan Zhao
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  4. Zude Zhou
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  5. Lin Zhang
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  6. Duc Truong Pham
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Corresponding author

Correspondence to Wenjun Xu .

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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Xu, W., Zhong, X., Zhao, Y., Zhou, Z., Zhang, L., Pham, D.T. (2017). Manufacturing Service Reconfiguration Optimization Using Hybrid Bees Algorithm in Cloud Manufacturing. 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_9

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  • DOI: https://doi.org/10.1007/978-3-319-61994-1_9

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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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