Dynamic and unified modelling of sustainable manufacturing capability for industrial robots in cloud manufacturing

  • Yuanyuan Zhao
  • Quan Liu
  • Wenjun Xu
  • Xingxing Wu
  • Xuemei Jiang
  • Zude Zhou
  • Duc Truong Pham


Industrial robots (IRs) are the important driving force to enable the production activities more automotive and highly efficient in modern manufacturing systems. However, in order to realize the effective employment and intelligent configuration of IRs in cloud manufacturing environment, it is required that the sustainable manufacturing capabilities of IRs can be described in a unified and formal manner. In this paper, a unified sustainable manufacturing capability (SMC) of the IR model is constructed in terms of functional attributes, structural information, activities and process condition. A hybrid logic description method integrating Ontology Web Language with dynamic description logic (DLL) is adopted to provide a semantical representation to both the static and dynamic characteristics of SMC. An interval-state description method is proposed to present energy consumption during the IR’s process in sections. Based on the constructed model, three types of rules are defined to reason the capability of IRs, including stability, energy consumption and production capacity. Finally, a cloud-based prototype system architecture is illustrated. An IR service platform is developed and implemented to verify the proposed model and the defined rules.


Industrial robots Sustainable manufacturing capability Dynamic and unified modelling Ontology Dynamic description logic 


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Copyright information

© Springer-Verlag London Ltd. 2017

Authors and Affiliations

  • Yuanyuan Zhao
    • 1
    • 2
  • Quan Liu
    • 1
    • 3
  • Wenjun Xu
    • 1
    • 2
  • Xingxing Wu
    • 1
    • 2
  • Xuemei Jiang
    • 1
    • 3
  • Zude Zhou
    • 1
    • 3
  • Duc Truong Pham
    • 4
  1. 1.School of Information EngineeringWuhan University of TechnologyWuhanChina
  2. 2.Hubei Key Laboratory of Broadband Wireless Communication and Sensor NetworksWuhan University of TechnologyWuhanChina
  3. 3.Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of EducationWuhan University of TechnologyWuhanChina
  4. 4.Department of Mechanical Engineering, School of EngineeringUniversity of BirminghamBirminghamUK

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