Requirements for a Big Data capturing and integration architecture in a distributed manufacturing scenario

被引:0
|
作者
Nino, Mikel [1 ]
Saenz, Fernando [2 ]
Miguel Blanco, Jose [1 ]
Illarramendi, Arantza [1 ]
机构
[1] Univ Basque Country, Dept Comp Languages & Syst, UPV EHU, San Sebastian, Spain
[2] Savvy Data Syst, San Sebastian, Spain
关键词
Big Data Analytics; Industry; 4.0; Smart Manufacturing; Cloud Computing; Predictive Analytics; Prescriptive Control; Decision-Guidance Systems; ANALYTICS;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Big Data is one of the key enabling technologies in smart manufacturing, where manufacturing companies aim at leveraging the data generated throughout their processes. The potential of Big Data Analytics is particularly significant in the context of manufacturing companies distributed worldwide. These companies own several manufacturing plants operating the same process in different environments and conditions. This generates massive amounts of data that could be analyzed in order to improve process efficiency and product quality. This paper presents the requirements for an architecture to capture, integrate and analyze the large-scale volumes of data generated in a real-world manufacturing business scenario -a chemical manufacturing sector distributed worldwide-. This scenario serves as a case study for an applied research project on Big Data Analytics. The business nature of this scenario provides those real-life requirements the architecture has to deal with. Existing approaches can be extended to fulfill these requirements, in order to be effectively applied in similar manufacturing business contexts.
引用
收藏
页码:1326 / 1329
页数:4
相关论文
共 50 条
  • [21] Capturing quality requirements of product family architecture
    Niemela, Eila
    Immonen, Anne
    INFORMATION AND SOFTWARE TECHNOLOGY, 2007, 49 (11-12) : 1107 - 1120
  • [22] An open Big Data Platform for Industry 4.0 - Requirements, architecture, applications
    Weskamp, Jan Nicolas
    Poudel, Bal Krishna
    Al-Gumaei, Khaled
    Pethig, Florian
    ATP MAGAZINE, 2019, (03): : 96 - 105
  • [23] Big Data-Based Attack Scenario Reconstruction Architecture in Smart Grid
    Guo, Liang
    Jin, Qianqian
    Liu, Ying
    Xia, Yuanyi
    Hu, Han
    COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS, CSPS 2018, VOL III: SYSTEMS, 2020, 517 : 1178 - 1187
  • [24] An architecture for distributed scenario building and evaluation
    Wild, RH
    Griggs, KA
    Li, EY
    COMMUNICATIONS OF THE ACM, 2005, 48 (11) : 80 - 86
  • [25] Study on Distributed Architecture, Information Integration and Access Control of Manufacturing Execution System
    Liu, Ling
    Yan, GuangRong
    Lei, Yi
    RESOURCES AND SUSTAINABLE DEVELOPMENT, PTS 1-4, 2013, 734-737 : 3207 - 3213
  • [26] Big data analytics architecture design-An application in manufacturing systems
    Fahmideh, Mandi
    Beydoun, Ghassan
    COMPUTERS & INDUSTRIAL ENGINEERING, 2019, 128 : 948 - 963
  • [27] A New Data Processing Architecture for Multi-Scenario Applications in Aviation Manufacturing
    Wang, Wei
    Fan, Lei
    Huang, Pu
    Li, Hai
    IEEE ACCESS, 2019, 7 : 83637 - 83650
  • [28] A new manufacturing resources integration and sharing modes in big data environment
    Xiang, Feng
    Chen, XiaoWu
    Jiang, GuoZhang
    PROCEEDINGS OF THE 2016 IEEE 11TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2016, : 1984 - 1987
  • [29] Data Integration in Manufacturing Industry Model-Based Integration of Data Distributed from ERP to PLC
    Hufnagel, Johann
    Vogel-Heuser, Birgit
    PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS (INDIN), 2015, : 275 - 281
  • [30] Distributed real-time ETL architecture for unstructured big data
    Mehmood, Erum
    Anees, Tayyaba
    KNOWLEDGE AND INFORMATION SYSTEMS, 2022, 64 (12) : 3419 - 3445