Architecture Design of Cloud CPS in Manufacturing

  • Lihui WangEmail author
  • Xi Vincent Wang


Cloud manufacturing is a new concept extending and adopting the concept of cloud computing for manufacturing. The aim is to transform manufacturing businesses to a new paradigm in that manufacturing capabilities and resources are componentised, integrated and optimised globally. This chapter presents an interoperable manufacturing perspective based on cloud manufacturing. A literature search has been undertaken regarding cloud architecture and technologies that can assist cloud manufacturing. Manufacturing resources and capabilities are discussed in terms of cloud services. A service-oriented, interoperable cloud manufacturing system is introduced. Service methodologies are developed to support two types of cloud users, i.e. customer user and enterprise user, along with standardised data models describing cloud service and relevant features. Two case studies are undertaken to evaluate the reported system. Cloud technology brings into manufacturing industry with a number of benefits such as openness, cost-efficiency, resource sharing and production scalability.


  1. 1.
    P. Mell, T. Grance, The NIST definition of cloud computing. NIST Spec. Publ. 800, 7 (2011)Google Scholar
  2. 2.
    P. Mell, T. Grance, Perspectives on Cloud Computing and Standards (National Institute of Standards and Technology (NIST), Information Technology Laboratory, 2009)Google Scholar
  3. 3.
    Apple, iCloud (2012, April). Available
  4. 4.
    Amazon, Amazon Elastic Compute Cloud (EC2) (2012, April). Available
  5. 5.
    Google, Google App Engine—Google Code (2012, Nov). Available
  6. 6.
    Microsoft, Windows Azure Platform_Microsoft Cloud Services (2012, Nov). Available
  7. 7.
    Oracle, Sun Cloud Developer Homepage (2012, Nov). Available
  8. 8.
    X. Xu, From Cloud Computing to Cloud Manufacturing. Robot. Comput. Integr. Manuf. 28, 75–86 (2012)CrossRefGoogle Scholar
  9. 9.
    F. Tao et al., Cloud Manufacturing: a Computing and Service-oriented Manufacturing Model. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 225, 1969–1976 (2011)CrossRefGoogle Scholar
  10. 10.
    B. Li et al., Cloud manufacturing: a new service-oriented networked manufacturing model. Comput. Integr. Manuf. Syst. 16, 1–7 (2010)Google Scholar
  11. 11.
    W. Terkaj et al., Virtual Factory Data Model in Proceedings of the Second International Workshop on Searching and Integrating New Web Data Sources (VLDS 2012), Istanbul, Turkey, 2012Google Scholar
  12. 12.
    M. Meier et al., ManuCloud: the next-generation manufacturing as a service environment. ERCIM News 83, 33–34 (2010)Google Scholar
  13. 13.
    O.E. Ruiz et al., EGCL: an extended g-code language with flow control, functions and mnemonic variables. World Acad. Sci. Eng. Technol. 67, 455–462 (2012)Google Scholar
  14. 14.
    A.L.K. Yip et al. A front-end system to support cloud-based manfuacturing of cutstomized products in Proceedings of the 9th International Conference on Manufacturing Research ICMR 2011, Glasgow, UK, 193–198, 2011Google Scholar
  15. 15.
    L. Wu, C. Yang, A solution of manufacturing resources sharing in cloud computing environment. Coop. Des. Vis. Eng. Lect Notes Comput. Sci. 6240, 247–252 (2010)CrossRefGoogle Scholar
  16. 16.
    C.S. Hu et al., Study of classification and modeling of virtual resources in cloud manufacturing. Appl. Mech. Mater. 121–126, 2274–2280 (2012)Google Scholar
  17. 17.
    Y.L. Luo et al., Study on multi-view model for cloud manufacturing. Adv. Mater. Res. 201, 685–688 (2011)CrossRefGoogle Scholar
  18. 18.
    Y.L. Luo et al., Research on the knowledge-based multi-dimensional information model of manufacturing capability in CMfg. Adv. Mater. Res. 472, 2592–2595 (2012)CrossRefGoogle Scholar
  19. 19.
    L. Zhang et al., Flexible Management of Resource Service Composition in Cloud Manufacturing, in Proceedings of the 2010 IEEE IEEM, 2278–2282, 2010Google Scholar
  20. 20.
    Q. Liu et al., Resource Management Based on Multi-agent Technology for Cloud Manufacturing, in International Conference on Electronics, Communications and Control (ICECC), Zhejiang, China, 2821–2824, 2011Google Scholar
  21. 21.
    W.H. Fan, T.Y. Xiao, Integrated Architecture of Cloud Manufacturing Based on Federation Mode. Comput. Integr. Manuf. Syst. 17, 469–476 (2011)Google Scholar
  22. 22.
    Y. Laili et al., A study of optimal allocation of computing resources in cloud manufacturing systems. Int. J. Adv. Manuf. Technol. 63, 1–20 (2012)CrossRefGoogle Scholar
  23. 23.
    X.V. Wang, X. Xu, ICMS: a cloud-based manufacturing system, in Cloud Manufacturing: Distributed Computing Technologies for Global and Sustainable Manufacturing, ed. by W. Li, J. Mehnen (Springer, 2012 in press)Google Scholar
  24. 24.
    G. Buonanno et al., Factors affecting ERP system adoption: a comparative analysis between SMEs and large companies. J. Enterp. Inf. Manag. 18, 384–426 (2005)CrossRefGoogle Scholar
  25. 25.
    T.F. Gattiker, D.L. Goodhue, What happens after ERP implementation: understanding the impact of interdependence and differentiation on plant-level outcomes. MIS Q. 29, 559–585 (2005)Google Scholar
  26. 26.
    D.G. Ko et al., Antecedents of knowledge transfer from consultants to clients in enterprise system implementations. MIS Q. 29, 59–85 (2005)Google Scholar
  27. 27.
    H. Liang et al., Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Q. 31, 59–87 (2007)Google Scholar
  28. 28.
    C.C. Wei et al., An AHP-based approach to ERP system selection. Int. J. Prod. Econ. 96, 47–62 (2005)CrossRefGoogle Scholar
  29. 29.
    A. Paulraj et al., Inter-organizational communication as a relational competency: antecedents and performance outcomes in collaborative buyer-supplier relationships. J. Oper. Manag. 26, 45–64 (2008)CrossRefGoogle Scholar
  30. 30.
    S.B. Modi, V.A. Mabert, Supplier development: improving supplier performance through knowledge transfer. J. Oper. Manag. 25, 42–64 (2007)CrossRefGoogle Scholar
  31. 31.
    M.P. Papazoglou, W.J. Van Den Heuvel, Service oriented architectures: approaches, technologies and research issues. VLDB J. 16, 389–415 (2007)CrossRefGoogle Scholar
  32. 32.
    L. Cherbakov et al., Impact of service orientation at the business level. IBM Syst. J. 44, 653–668 (2005)CrossRefGoogle Scholar
  33. 33.
    M.T. Schmidt et al., The enterprise service bus: making service-oriented architecture real. IBM Syst. J. 44, 781–797 (2005)CrossRefGoogle Scholar
  34. 34.
    P. Rauyruen, K.E. Miller, Relationship quality as a predictor of B2B customer loyalty. J. Bus. Res. 60, 21–31 (2007)CrossRefGoogle Scholar
  35. 35.
    P.A. Bernstein, S. Melnik, Model Management 2.0: Manipulating Richer Mappings. Presented at the SIGMOD 07’ international conference on management of Data, Beijing, China, 2007Google Scholar
  36. 36.
    ISO, ISO 10303 -1, Industrial Automation Systems and Integration—Product Data Representation and Exchange—Part 1: Overview and Fundamental Principles. (ISO, Geneva, 1994)Google Scholar
  37. 37.
    ISO 14649-1, Industrial Automation Systems and Integration—Physical Device Control—Data Model for Computerized Numerical Controllers—Part 1: Overview and Fundamental Principles, 2003Google Scholar
  38. 38.
    W. Gielingh, An assessment of the current state of product data technologies. CAD Comput. Aided Des. 40, 750–759 (2008)CrossRefGoogle Scholar
  39. 39.
    L. Zhang et al., Key technologies for the construction of manufacturing cloud. Comput. Integr. Manuf. Syst. 16, 2510–2520 (2010)Google Scholar
  40. 40.
    R.D. Allen et al., The application of STEP-NC using agent-based process planning. Int. J. Prod. Res. 43, 655–670 (2005)CrossRefzbMATHGoogle Scholar
  41. 41.
    L. Monostori et al., Agent-based systems for manufacturing. Ann. CIRP 55, 697–720 (2006)CrossRefGoogle Scholar
  42. 42.
    A. Nassehi et al., The application of multi-agent systems for STEP-NC computer aided process planning of prismatic components. Int. J. Mach. Tools Manuf. 46, 559–574 (2006)CrossRefGoogle Scholar
  43. 43.
    H. Panetto, A. Molina, Enterprise Integration and Interoperability in Manufacturing Systems: trends and Issues. Comput. Ind. 59, 641–646 (2008)CrossRefGoogle Scholar
  44. 44.
    M. Sadeghi et al., A collaborative platform architecture for coherence management in multi-view integrated product modelling. Int. J. Comput. Integr. Manuf. 23, 270–282 (2010)CrossRefGoogle Scholar
  45. 45.
    A.J. Álvares et al., An Integrated Web-based CAD/CAPP/CAM system for the remote design and manufacture of feature-based cylindrical parts. J. Intell. Manuf. 19, 643–659 (2008)CrossRefGoogle Scholar
  46. 46.
    C. Brecher et al., Module-based Platform for Seamless Interoperable CAD-CAM-CNC Planning, in Advanced Design and Manufacturing Based on STEP, ed. by X.W. Xu, A.Y.C. Nee (London: Springer, 439–462, 2009)Google Scholar
  47. 47.
    S.C. Oh, S.T. Yee, Manufacturing interoperability using a semantic mediation. Int. J. Adv. Manuf. Technol. 39, 199–210 (2008)CrossRefGoogle Scholar
  48. 48.
    Y. Zhang et al., Understanding the STEP-NC data model for computer numerical control, in Advanced Computer Control (ICACC), 2nd International Conference on, 2010, 300–304Google Scholar
  49. 49.
    O.F. Valilai, M. Houshmand, INFELT STEP: an integrated and interoperable platform for collaborative CAD/CAPP/CAM/CNC machining systems based on STEP standard. Int. J. Comput. Integr. Manuf. 23, 1095 (2010)CrossRefGoogle Scholar
  50. 50.
    J. Yang et al., OpenPDM-based product data exchange among heterogeneous pdm systems in a distributed environment. Int. J. Adv. Manuf. Technol. 40, 1033–1043 (2009)CrossRefGoogle Scholar
  51. 51.
    S. Makris et al., On the information modeling for the electronic operation of supply chains: a maritime case study. Robot. Comput. Integr. Manuf. 24, 140–149 (2008)CrossRefGoogle Scholar
  52. 52.
    G. Chryssolouris et al., Towards the Internet based supply chain management for the ship repair industry. Int. J. Comput. Integr. Manuf. 17, 45–57 (2004)CrossRefGoogle Scholar
  53. 53.
    D. Mavrikios et al., A New concept for collaborative product and process design within a human-oriented collaborative manufacturing environment. Future Prod. Dev. 301–310 (2007)Google Scholar
  54. 54.
    M. Pappas et al., A Collaboration Platform for Product Design Evaluation, Demonstration and Customization. Presented at the IFAC workshop on manufacturing modelling, management and control, Budapest, Hungary, 2007Google Scholar
  55. 55.
    S. Makris, K. Alexopoulos, AutomationML server-A prototype data management system for multi disciplinary production engineering. Procedia CIRP 2, 22–27 (2012)CrossRefGoogle Scholar
  56. 56.
    B. Asiabanpour et al., An overview on five approaches for translating CAD data into manufacturing information. J. Adv. Manuf. Syst. 8, 89–114 (2009)CrossRefGoogle Scholar
  57. 57.
    S.T. Newman et al., Strategic advantages of interoperability for global manufacturing using CNC technology. Robot. Comput. Integr. Manuf. 24(2008), 699–708 (2008)CrossRefGoogle Scholar
  58. 58.
    A. Nassehi et al., Toward interoperable CNC manufacturing. Comput. Integr. Manuf. 21, 222–230 (2008)CrossRefGoogle Scholar
  59. 59.
    S.T. Newman, A. Nassehi, Universal manufacturing platform for CNC machining. Ann. CIRP 56, 459 (2007)CrossRefGoogle Scholar
  60. 60.
    A. Mokhtar, M. Houshmand, Introducing a roadmap to implement the universal manufacturing platform using axiomatic design theory. Int. J. Manuf. Res. 5, 252–269 (2010)CrossRefGoogle Scholar
  61. 61.
    P. Vichare et al., A unified manufacturing resource model for representation of computerized numerically controlled machine tools. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 223, 463–483 (2009)CrossRefGoogle Scholar
  62. 62.
    N. Do, G. Chae, A product data management architecture for integrating hardware and software development. Comput. Ind. 62, 854–863 (2011)CrossRefGoogle Scholar
  63. 63.
    J. Hwang et al., Representation and propagation of engineering change information in collaborative product development using a neutral reference model. Concur. Eng. 17, 147–157 (2009)CrossRefGoogle Scholar
  64. 64.
    S.S. Choi et al., XML-based neutral file and PLM integrator for PPR information exchange between heterogeneous PLM systems. Int. J. Comput. Integr. Manuf. 23, 216–228 (2010)CrossRefGoogle Scholar
  65. 65.
    R. Jardim-Goncalves et al., Knowledge framework for intelligent manufacturing systems. J. Intell. Manuf. 22, 725–735 (2011)CrossRefGoogle Scholar
  66. 66.
    ISO 10303-236, Industrial Automation Systems and Integration—Product Data Representation and Exchange—Part 236: Application Protocol: Furniture Catalog and Interior Design, (2003)Google Scholar
  67. 67.
    B.C. Kim et al., Web service with parallel processing capabilities for the retrieval of cad assembly data. Concur. Eng. Res. Appl. 19, 5–18 (2011)CrossRefGoogle Scholar
  68. 68.
    STEP Tools, ST-Developer—STEP Tools, Inc (2011, Nov). Available
  69. 69.
    Y. Kikuchi et al., PDQ (Product Data Quality): representation of data quality for product data and specifically for shape data. J. Comput. Inf. Sci. Eng. 10, 1–8 (2010)CrossRefGoogle Scholar
  70. 70.
    M. Graube et al., Linked Data as Integrating Technology for Industrial Data, in 2011 International Conference on Network-Based Information Systems (NBiS), Tirana, Albania, 162–167, 2011Google Scholar
  71. 71.
    J.Y. Lee et al., NESIS: A neutral schema for a web-based simulation model exchange service across heterogeneous simulation software. Int. J. Comput. Integr. Manuf. 24, 948–969 (2011)CrossRefGoogle Scholar
  72. 72.
    I.-H. Song et al., Development of a lightweight CAE middleware for CAE data exchange. Int. J. Comput. Integr. Manuf. 22, 823–835 (2009)CrossRefGoogle Scholar
  73. 73.
    Q. Li et al., Towards the business-information technology alignment in cloud computing environment: an approach based on collaboration points and agents. Int. J. Comput. Integr. Manuf. 24, 1038–1057Google Scholar
  74. 74.
    ISO, ISO 10303-11, Industrial Automation Systems and Integration—Product Data Representation and Exchange—Part 11: Description Methods: The EXPRESS Language Reference Manual (2004)Google Scholar
  75. 75.
    ISO 10303-21, Industrial Automation Systems and Integration—Product Data Representation and Exchange—Part 21: Implementation Methods: Clear Text Encoding of the Exchange Structure (2002)Google Scholar
  76. 76.
    G. Hu et al., Cloud robotics: architecture, challenges and applications. Netw. IEEE 26, 21–28 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Production EngineeringKTH Royal Institute of TechnologyStockholmSweden

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