Abstract
In today’s competitive markets where it is essential to provide high-quality results in order to cope up with the enormous and ever-growing demand for manufacturing resources, selection of optimal Cloud Manufacturing service provider and efficient service scheduling is the core of achieving high-quality and prompt outcomes. This paper elaborates on the use of recommender system to filter out the best candidate CMfg service provider based on various factors in a distributed model for an easily adaptable framework. This work is probably valuable for future research on the selection criterion of service providers and improving the efficiency of CMfg process as a whole.
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Zhang, Y., Zhang, G., Liu, Y., et al.: Research on services encapsulation and virtualization access model of machine for cloud manufacturing. J. Intell. Manuf. 28, 1109–1123 (2017). https://doi.org/10.1007/s10845-015-1064-2
Cheng, Y., Tao, F., Zhao, D., Zhang, L.: Modeling of manufacturing service supply-demand matching hypernetwork in service-oriented manufacturing systems. Robot. Comput. Integr. Manuf. 45, 59–72 (2017). https://doi.org/10.1016/j.rcim.2016.05.007
Shen, X., Yao, X.: Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems. Inform. Sci. 298, 198–224 (2015). https://doi.org/10.1016/j.ins.2014.11.036
Wang, S., Guo, L., Kang, L., et al.: Research on selection strategy of machining equipment in cloud manufacturing. Int. J. Adv. Manuf. Technol. 71(9–12), 1549–1563 (2014). https://doi.org/10.1007/s00170-013-5578-5
Liu, W., Liu, B., Sun, D., Li, Y., Ma, G.: Study on multi-task oriented services composition and optimisation with the ‘Multi-Composition for Each Task’ pattern in cloud manufacturing systems. Int. J. Comput. Integr. Manuf. 26(8), 786–805 (2013). https://doi.org/10.1080/0951192x.2013.766939
Li, B., et al.: Cloud manufacturing: a new service-oriented networked manufacturing model. Comput. Integr. Manuf. Syst. 16(1), 1–7 (2010)
Xu, X.: From cloud computing to cloud manufacturing. Robot. Comput. Integr. Manuf 28(1), 75–86 (2012). https://doi.org/10.1016/j.rcim.2011.07.002
Zhang, L., et al.: Cloud manufacturing: a new manufacturing paradigm. Ent. Inform. Syst. 8(2), 167–187 (2014). https://doi.org/10.1080/17517575.2012.683812
He, W., Xu, L.: A state-of-the-art survey of cloud manufacturing. Int. J. Comput. Integr. Manuf 28(3), 239–250 (2015). https://doi.org/10.1080/0951192x.2013.874595
Chen, J., Huang, G.Q., Wang, J.-Q., Yang, C.: A cooperative approach to service booking and scheduling in cloud manufacturing. Eur. J. Oper. Res 273(3), 861–873 (2019). https://doi.org/10.1016/j.ejor.2018.09.007
Tao, F., Zhang, L., Liu, Y., Cheng, Y., Wang, L., Xu, X.: Manufacturing service management in cloud manufacturing: overview and future research directions. J. Manuf. Sci. Eng. 137(4), 040912–040923 (2015). https://doi.org/10.1115/1.4030510
Tao, F., LaiLi, Y., Xu, L., Zhang, L.: FC-PACO-RM: a parallel method for service composition optimal-selection in cloud manufacturing system. IEEE Trans. Ind. Inform 9(4), 2023–2033 (2013). https://doi.org/10.1109/tii.2012.2232936
Tao, F., Cheng, J., Cheng, Y., Gu, S., Zheng, T., Yang, H.: SDMSim: a manufacturing service supply-demand matching simulator under cloud environment. Robot. Comput. Integr. Manuf. 45, 34–46 (2017). https://doi.org/10.1016/j.rcim.2016.07.001
Chen, T.: Strengthening the competitiveness and sustainability of a semiconductor manufacturer with cloud manufacturing. Sustainability 6, 251–266 (2014). https://doi.org/10.3390/su6010251
He, W., Jia, G., Zong, H., Kong, J.: Multi-objective service selection and scheduling with linguistic preference in cloud manufacturing. Sustain. Sci. Pract. Policy 11(9), 2619 (2019). https://doi.org/10.3390/su11092619
Zhou, L., Zhang, L., Zhao, C., Laili, Y., Xu, L.: Diverse task scheduling for individualized requirements in cloud manufacturing. Ent. Inf. Sys. 12(3), 300–318 (2018). https://doi.org/10.1080/17517575.2017.1364428
Wu, D., 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). https://doi.org/10.1016/j.jmsy.2013.04.008
Liu, Y., Xu, X., Zhang, L., Wang, L., Zhong, R.Y.: Workload-based multi-task scheduling in cloud manufacturing. Robot. Comput. Integr. Manuf. 45, 3–20 (2017). https://doi.org/10.1016/j.rcim.2016.09.008
Škulj, G., Vrabič, R., Butala, P., Sluga, A.: Decentralised network architecture for cloud manufacturing. Int. J. Comput. Integr. Manuf. 30(4–5), 395–408 (2017). https://doi.org/10.1080/0951192x.2015.1066861
Tao, J., Zhang, S., Yang, D.: The safety detection for double tapered roller bearing based on deep learning. In: Wang, G., Chen, J., Yang, Laurence T. (eds.) SpaCCS 2018. LNCS, vol. 11342, pp. 485–496. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-05345-1_42
Barenji, A.V., Barenji, R.V., Roudi, D., et al.: A dynamic multi-agent-based scheduling approach for SMEs. Int. J. Adv. Manuf. Technol. 89(9–12), 3123–3137 (2017). https://doi.org/10.1007/s00170-016-9299-4
Alinani, K., Wang, G., Alinani, A., Hussain, D., Forrest, M.: Aggregating author profiles from multiple publisher networks to build author knowledge graph, pp. 1414–1421 (2018). https://doi.org/10.1109/smartworld.2018.00245
Acknowledgments
The work described in this paper is supported in part by National Natural Science Foundation of China under Grants 61632009 & 61876062, in part by the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006, High-Level Talents Program of Higher Education in Guangdong Province under Grant 2016ZJ01, and the postdoctoral funding of Hunan University of Science and Technology, funding number 903-E61804.
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Alinani, K., Liu, D., Zhou, D., Wang, G. (2019). Recommender System for Decentralized Cloud Manufacturing. In: Wang, G., Bhuiyan, M.Z.A., De Capitani di Vimercati, S., Ren, Y. (eds) Dependability in Sensor, Cloud, and Big Data Systems and Applications. DependSys 2019. Communications in Computer and Information Science, vol 1123. Springer, Singapore. https://doi.org/10.1007/978-981-15-1304-6_14
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