An evolutionary data model for the implementation of collective cloud manufacturing to maintain individual value-added networks

被引:1
|
作者
Strljic, Matthias Milan [1 ]
Riedel, Oliver [1 ]
机构
[1] Univ Stuttgart, Inst Control Engn Machine Tools & Mfg Units ISW, Stuttgart, Germany
关键词
Cloud Manufacturing; Ontology; Service-oriented manufacturing; Product data model; THE-ART SURVEY;
D O I
10.1109/concapanxxxix47272.2019.8976942
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Cloud Manufacturing (CM) offers the possibility to use and provide production services within an as-a-service concept. The CM paradigm enables more efficient resource utilization in the context of industry 4.0 through fully automated order processing. Existing architecture solutions, however, follow a central platform approach with a global neutral data model. As a consequence, the individuality of companies within the CM is not given any room for expression and symbioses between companies are not established. The result is a disadvantage particularly for SMEs, which generate their competitive advantage from innovative production technologies and symbiotic connections with customers and other SMEs. The focus of Collective Cloud Manufacturing (CCM) is the preservation of these characteristics, in which an over-approximation of costs through the integration of production-related simulations is to be reduced and the data security of the customer is to be enhanced. So in this work, a data model for an existing concept for CCM is presented. The requirements for the data model and the runtime behavior are defined. Subsequently, the state of the art of existing models in the domain of CM is presented. The developed data model is presented with an application evaluation.
引用
收藏
页码:392 / 397
页数:6
相关论文
共 13 条
  • [1] A hybrid model for value-added process analysis of manufacturing value chains
    Song, Jingwen
    Wang, Aihui
    Liu, Ping
    Li, Daming
    Han, Xiaobo
    Yan, Yuhao
    IET COLLABORATIVE INTELLIGENT MANUFACTURING, 2023, 5 (01)
  • [2] The Strategies of the Manufacturing Service Industry: The Perspective of Value-added Chain Model
    Yang, Phil Y.
    Chang, Yuan-Chieh
    Yang, Yi-Chang
    Wang, Jian-Han
    2011 PROCEEDINGS OF PICMET 11: TECHNOLOGY MANAGEMENT IN THE ENERGY-SMART WORLD (PICMET), 2011,
  • [3] The rise of the manufacturing service industry: the perspective of value-added chain model
    Yang, Phil Yihsing
    Luo, Lieh-Ming
    Li, Chun-Sheng Joseph
    Yang, Yi-Chang
    Lee, Sandra H. T.
    CHINESE MANAGEMENT STUDIES, 2013, 7 (03) : 403 - 418
  • [4] Investment decision of value-added service of cloud manufacturing platform under users lacking information
    Gui Y.
    Hu H.
    Gong B.
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2022, 28 (04): : 1211 - 1219
  • [5] Petri Net model of repetitive push manufacturing with Polca to minimise value-added WIP
    Aziz, M. H.
    Bohez, Erik L. J.
    Pisuchpen, Roongrat
    Parnichkun, Manukid
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2013, 51 (15) : 4464 - 4483
  • [6] A Proposal of Standardised Data Model for Cloud Manufacturing Collaborative Networks
    Andres, Beatriz
    Sanchis, Raquel
    Poler, Raul
    Saari, Leila
    COLLABORATION IN A DATA-RICH WORLD, 2017, 506 : 77 - 85
  • [7] Using Digital Twin Data for the Attribute-Based Usage Control of Value-Added Networks
    Kern, Alexander
    Anderl, Reiner
    2020 SEVENTH INTERNATIONAL CONFERENCE ON SOFTWARE DEFINED SYSTEMS (SDS), 2020, : 29 - 36
  • [8] A Correlated Random Effects Model for Nonignorable Missing Data in Value-Added Assessment of Teacher Effects
    Karl, Andrew T.
    Yang, Yan
    Lohr, Sharon L.
    JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 2013, 38 (06) : 577 - 603
  • [9] Accessing GOES-R Series data from cloud platforms to create a value-added tool for end users
    Losos, Danielle
    Pitts, Katherine
    McHugh, Maurice
    EARTH OBSERVING SYSTEMS XXV, 2020, 11501
  • [10] The model research of electric power information trading value-added service under the background of big data
    He Yang
    Shang Jincheng
    Dai Yong
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON CIVIL, TRANSPORTATION AND ENVIRONMENT, 2016, 78 : 1295 - 1299