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An autonomy-oriented method for service composition and optimal selection in cloud manufacturing

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Abstract

Since the emergence of cloud manufacturing (CMfg), service composition and optimal selection (SCOS) has been focused on as the core issue of service reconfiguration and supply-demand joining. In view of limitations of existing centralized mode, this paper studies autonomy-oriented SCOS method in CMfg. At first, initiative-based service operation procedures are specified and followed by the definition of correlation-aware composition strategy. Then, service responses are integrated with their trust to produce execution prospects which is the trustworthy basis of SCOS. Fuzzy soft set-based decision making method enhanced with volatility analysis is proposed. After trust-based service filtration, flexible and balanced optimal selection is carried out based on level soft sets and with volatility analysis improving discrimination. A numerical case illustrates the method of this paper, and discussions of key means are given at last.

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Acknowledgements

This research is supported by grants from the Social Science Planning Project of Shandong Province (Grant No. 15CGLJ25) and the Humanities and Social Sciences Project for Colleges of Shandong Province (Grant No. J14WG25).

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Authors and Affiliations

  1. School of Humanities and Economic Management, China University of Geosciences, Beijing, 100083, People’s Republic of China

    Changyi Li, Jianhe Guan & Ning Ma

  2. Business School, Shandong University of Technology, Zibo, 255000, People’s Republic of China

    Changyi Li, Tingting Liu & Jun Zhang

  3. School of Information Engineering, China University of Geosciences, Beijing, 100083, People’s Republic of China

    Jianhe Guan

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  1. Changyi Li
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  2. Jianhe Guan
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  3. Tingting Liu
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Correspondence to Jianhe Guan.

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Li, C., Guan, J., Liu, T. et al. An autonomy-oriented method for service composition and optimal selection in cloud manufacturing. Int J Adv Manuf Technol 96, 2583–2604 (2018). https://doi.org/10.1007/s00170-018-1746-y

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