An interoperable knowledge base for manufacturing resource and service capability

被引:0
|
作者
Zhao Y. [1 ]
Liu Q. [1 ]
Xu W. [1 ]
Xu X.W. [2 ]
Yu S. [2 ]
Zhou Z. [3 ]
机构
[1] School of Information Engineering, Wuhan University of Technology, Wuhan
[2] Department of Mechanical Engineering, University of Auckland, Auckland
[3] School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan
基金
中国国家自然科学基金;
关键词
Cloud manufacturing; Knowledge base; Manufacturing resource capability; Manufacturing service; Ontology web language; OWL; Semantic web rule language; SWRL;
D O I
10.1504/IJMR.2017.083650
中图分类号
学科分类号
摘要
To realise collaborative utilisation of resource in cloud manufacturing, in this paper, an interoperable knowledge base of manufacturing resource and service capability (IKB-MRSC) is developed for service discovery and selection. First, a network-based structural knowledge model is constructed including items set, links set and rule set. The functional entities in STEP/STEP-NC are integrated with status information and expert experience to form the items set. Links set and rule set are defined. Based on this, an upper-level manufacturing service model is built including capability profile, process model and resource model. Then, OWL and SWRL are combined to offer the semantic and logic representation for knowledge model. OntoSTEP is adopted to transfer EXPRESS-based schema into ontology pattern. Rules are defined for reasoning service capability with its related resource capability. Underlying this, a triple-level service matchmaking strategy is proposed. Finally, implementation verifies the validity of the knowledge base. Copyright © 2017 Inderscience Enterprises Ltd.
引用
收藏
页码:20 / 43
页数:23
相关论文
共 50 条
  • [31] Composition modeling for manufacturing resource cloud service
    Yi, Guodong
    Hu, Hangjian
    Zhang, Shuyou
    Sun, Longfei
    SERVICE ORIENTED COMPUTING AND APPLICATIONS, 2020, 14 (02) : 135 - 147
  • [32] Assessment and selection for capability resource demand in cloud manufacturing environment
    Chen Y.
    Liu C.
    Yang W.
    Yang X.
    Liu, Chuanbiao (18883724748@163.com), 1600, CIMS (23): : 2304 - 2312
  • [33] Composition modeling for manufacturing resource cloud service
    Guodong Yi
    Hangjian Hu
    Shuyou Zhang
    Longfei Sun
    Service Oriented Computing and Applications, 2020, 14 : 135 - 147
  • [34] Demand-based manufacturing service capability estimation of a manufacturing system in a social manufacturing environment
    Cao, Wei
    Jiang, Pingyu
    Jiang, Kaiyong
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2017, 231 (07) : 1275 - 1297
  • [35] An interoperable solution for Cloud manufacturing
    Wang, Xi Vincent
    Xu, Xun W.
    ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2013, 29 (04) : 232 - 247
  • [36] The service-oriented, interoperable and knowledge-sharing architecture for ship specifications
    Cheng, Yune-Yu
    Shaw, Heiu-Jou
    Lai, Hsin-His
    INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2011, 24 (12) : 1136 - 1151
  • [37] The impact of customer knowledge capability and relational capability on new service development performance: The case of health service
    Weng, Rhay-Hung
    Huang, Ching-Yuan
    JOURNAL OF MANAGEMENT & ORGANIZATION, 2012, 18 (05) : 608 - 624
  • [38] Multi-objective optimization for manufacturing service composition with service capability constraints
    Luo, He
    Wu, Ping
    Wang, Bo
    Cai, Zhiming
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2024, 30 (12): : 4508 - 4524
  • [39] Development of Knowledge Base for Sheet Metal Manufacturing
    Ausmanas, N.
    Bargelis, A.
    MECHANIKA 2012: PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE, 2012, : 16 - 20
  • [40] An Optimal Service-Selection Model Based On Capability and Quality of Resource Service
    Zhang, Xiaodong
    Zhan Dechen
    Nie, Lanshun
    Zhao, Tianqi
    Xiong, Xiao
    PROCEEDINGS 2014 INTERNATIONAL CONFERENCE ON SERVICE SCIENCES (ICSS 2014), 2014, : 47 - 52