Abstract
Efficient solution for Cloud Manufacturing (CMfg) service optimal-selection plays an increasing critical part in CMfg systems as an ever-growing number of CMfg services are aggregating in a CMfg platform. In most current methods, a set of relatively fixed quality of service (QoS) indicators are adopted to deal with the optimal-selection for different types of CMfg services. However, this often leads to low accuracy and flexibility, especially when cloud users’ requirements involve different CMfg services with respective individualized characteristics. This paper presents evaluation metrics pool based CMfg service selection model (CSS-P), a framework of CMfg service selection that introduces an evaluation metrics pool as well as a new service selection mechanism based on adaptive variable evaluation metrics. Adaptive individualized metrics contribute to improving the accuracy and flexibility of CMfg service matching and selection, and better meet the customized needs of cloud users.
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References
Ren, L., Zhang, L., Wang, L.H., Tao, F., Chai, X.D.: Cloud manufacturing: key characteristics and applications. Int. J. Comput. Integr. Manuf. (2014). doi:10.1080/0951192X.2014.902105
Li, B.H., Zhang, L., Ren, L., Chai, X.D., Tao, F., Luo, Y.L., Wang, Y.Z., Yin, C., Huang, G., Zhao, X.P.: Further discussion on cloud manufacturing. Comput. Integr. Manuf. Syst. 17(3), 449–457 (2011). doi:10.13196/j.cims.2011.03.3.libh.004
Li, B.H., Zhang, L., Ren, L., Chai, X.D., Tao, F., Wang, Y.Z., Yin, C., Huang, P., Zhao, X.P., Zhou, Z.D.: Typical characteristics, technologies and applications of cloud manufacturing. Comput. Integr. Manuf. Syst. 18(7), 1345–1356 (2012). doi:10.13196/j.cims.2012.07.4.libh.006
Zhang, L., Luo, Y.L., Tao, F., Li, B.H., Ren, L., Zhang, X.S., Guo, H., Cheng, Y., Hu, A.R.: Cloud manufacturing: a new manufacturing paradigm. Enterp. Inf. Syst. (2012). doi:10.1080/17517575.2012.683812
Adamson, G., Wang, L H., Holm, M.: The state of the art of cloud manufacturing and future trends. In: ASME 2013 International Manufacturing Science and Engineering Conference collocated with the 41st North American Manufacturing Research Conference (2013). doi: 10.1115/MSEC2013-1123
Ren, L., Zhang, L., Tao, F., Zhao, C., Chai, X.D., Zhao, X.P.: Cloud manufacturing: from concept to practice. Enterp. Inf. Syst. (2013). doi:10.1080/17517575.2013.839055
Wu, D.Z., Greer, M.J., Rosen, D.W., Schaefer, D.: Cloud manufacturing: strategic vision and state-of-the-art. J. Manuf. Syst. 32(4), 564–579 (2013). doi:10.1016/j.jmsy.2013.04.008
He, W., Xu, L.D.: A state-of-the-art survey of cloud manufacturing. Int. J. Comput. Integr. Manuf. 28(3), 239–250 (2015). doi:10.1080/0951192X.2013.874595
Huang, B.Q., Li, C.H., Tao, F.: A chaos control optimal algorithm for QoS-based service composition selection in cloud manufacturing system. Enterp. Inf. Syst. 8(4), 445–463 (2014). doi:10.1080/17517575.2013.792396
Cui, J., Ren, L., Zhang, L., Wu, Q.: An optimal allocation method for virtual resource considering variable metrics of cloud manufacturing service. In: ASME 2015 International Manufacturing Science and Engineering Conference (2015). doi: 10.1115/MSEC2015-9245
Cheng, Y., Tao, F., Liu, Y.L., Zhao, D.M., Zhang, L., Xu, L.D.: Energy-aware resource service scheduling based on utility evaluation in cloud manufacturing system. In: Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, pp. 1–15 (2013). doi: 10.1177/0954405413492966
Xiang, F., Hu, Y.F., Yu, Y.R., Wu, H.C.: QoS and energy consumption aware service composition and optimal-selection based on Pareto group leader algorithm in cloud manufacturing system. Cent. Eur. J. Oper. Res. 22(4), 663–685 (2013). doi:10.1007/s10100-013-0293-8
Tao, F., Hu, Y.F., Zhou, Z.D.: Application and modeling of resource service trust-QoS evaluation in manufacturing grid system. Int. J. Prod. Res. 47(6), 1521–1550 (2009). doi:10.1080/00207540701551927
Laili, Y.J., Tao, F., Zhang, L., Sarker, B.R.: A study of optimal allocation of computing resources in cloud manufacturing systems. Int. J. Adv. Manuf. Technol. 63(5–8), 671–690 (2012). doi:10.1007/s00170-012-3939-0
Ren, L., Cui, J., Wei, Y.C., Laili, Y.J., Zhang, L.: Research on the impact of service provider cooperative relationship on cloud manufacturing platform. Int. J. Adv. Manuf. Technol. (2016). doi:10.1007/s00170-016-8345-6
Acknowledgements
The research is supported by the National High-Tech Research and Development Plan of China under grant No. 2015AA042101, the Natural Science Foundation of Beijing under grant No. 4142031, the National Science Foundation of China under grant No. 61572057 and the Fund of State Key Laboratory of Intelligent Manufacturing System Technology in China.
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Cui, J., Ren, L., Zhang, L. (2016). Cloud Manufacturing Service Selection Model Based on Adaptive Variable Evaluation Metrics. In: Zhang, L., Song, X., Wu, Y. (eds) Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim SCS AutumnSim 2016 2016. Communications in Computer and Information Science, vol 645. Springer, Singapore. https://doi.org/10.1007/978-981-10-2669-0_2
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DOI: https://doi.org/10.1007/978-981-10-2669-0_2
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