Abstract
Manufacturing plays an important role in the development of national economy. Intelligent manufacturing is the integration of modern business management model, information technology and the traditional manufacturing industry. This paper proposes to handle the following problems that intelligent manufacturing industry faced: (1) the problem of classification and composition of services of different granularity level, (2) the achieve of intelligent logistics over the cross-regional production process, (3) the need of an efficient and stable algorithm for services selection. To achieve cross-regional logistics intelligently and to provide service more intelligently, this paper classify services into five categories according to the level of granularity, and logistics services as the sixth. We design a service ontology based on owl. At last, we design a service selection mode based on the descent of granularity level and a peer service priority-based algorithm for service selection.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bo-hu, L.I., Zhang, L., Wang, S.L., et al.: Cloud manufacturing: a new service-oriented networked manufacturing model. J. Comput. Integr. Manufact. Syst. 16, 1–1343 (2010)
Liu, Q., Wan, J., Zhou, K.: Cloud manufacturing service system for industrial-cluster-oriented application. J. Internet Technol. 15(3), 373–380 (2014)
Wang, S., Wan, J., Li, D., Zhang, C.: Implementing smart factory of industrie 4.0: an outlook. Int. J. Distrib. Sens. Netw. 2016, 10 (2016). doi:10.1155/2016/3159805. Article ID 3159805
Wei, C.M., Zhang, C.L., Song, T.X., Huang, B.Q.: A cloud manufacturing service management model and its implementation. In: Proceedings of International Conference on Service Sciences, vol. 3, pp. 60–63 (2013)
Jin, Z.X.: Research on solutions of cloud manufacturing in automotive industry. In: SAE-China, FISITA (eds.) Lecture Notes in Electrical Engineering, vol. 199, pp. 225–234 (2013)
Wang, J., Wang, J., Tao, Y.Z., Li, H.M., Li, W., Jiang, L.Q.: The exploration of cloud manufacturing service mode for high power laser optical elements. In: Proceedings of the SPIE International Society Optical Engineering (2012)
Chen, T.: Strengthening the competitiveness and sustainability of a semiconductor manufacturer with cloud manufacturing. J. Sustain. 6, 251–266 (2014)
Liu I, Jiang H.: Research on key technologies for design services collaboration in cloud manufacturing. In: 16th IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 824–829 IEEE (2012)
Cheng, Y., Zhang, Y., Lv, L., Liu, J.R., Tao, F., Zhang, L.: Analysis of cloud service transaction in cloud manufacturing. In: IEEE International Conference on Industrial Informatics, pp. 320–325 (2012)
Tao, F., Zuo, Y., Xu, L.D., et al.: IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. J. IEEE Trans. Ind. Inform. 10, 1547–1557 (2014)
Wang, L.: Machine availability monitoring and machining process planning towards Cloud manufacturing. CIRP J. Manufact. Sci. Technol. 6, 263–273 (2013)
Liu, X., Li, Y., Wang, L.: A cloud manufacturing architecture for complex parts machining. J. Manufact. Sci. Eng. 137, 061009 (2014)
Cao, Y., Wang, S., Kang, L., et al.: Study on machining service modes and resource selection strategies in cloud manufacturing. Int. J. Adv. Manufact. Technol. pp. 1–17 (2015)
Liu, Z.Z., Chu, D.H., Song, C., et al.: Social learning optimization (SLO) algorithm paradigm and its application in QoS-aware cloud service composition. Inf. Sci. Int. J. 326, 315–333 (2016)
Gabrel, V., Manouvrier, M., Murat, C.: Web services composition: complexity and models. J. Discrete Appl. Math. 196, 67–82 (2014)
Liu, W., Liu, B., Sun, D., et al.: 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. Manufact. 26, 786–805 (2013)
Huang, B., Tao, C.L.F.: A chaos control optimal algorithm for QoS-based service composition selection in cloud manufacturing system. J. Enterp. Inf. Syst. 8, 445–463 (2014)
Vahit, K.: Lu V. An object-oriented approach for multi-objective flexible job-shop scheduling problem. Expert Syst. Appl. Int. J. 45, 71–84 (2016)
Acknowledgments
This paper is supported by Science and Technology Planning Project of Guangdong Province, China (2014B090921007), Science and Technology Program of Guangzhou, China (20150810068), Science and Technology program of Haizhu District, China (2014-cg-02).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Chen, X., Zhang, P., Liang, W., Li, F. (2016). Service Model and Service Selection Strategies for Cross-regional Intelligent Manufacturing. In: Wan, J., Humar, I., Zhang, D. (eds) Industrial IoT Technologies and Applications. Industrial IoT 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 173. Springer, Cham. https://doi.org/10.1007/978-3-319-44350-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-319-44350-8_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44349-2
Online ISBN: 978-3-319-44350-8
eBook Packages: Computer ScienceComputer Science (R0)