Data Analytics in Industry 4.0: A Survey

被引:52
|
作者
Duan, Lian [1 ]
Xu, Li Da [2 ]
机构
[1] Hofstra Univ, Dept Informat Syst & Business Analyt, Hempstead, NY 11550 USA
[2] Old Dominion Univ, Dept Informat Technol & Decis Sci, Norfolk, VA USA
关键词
Industry; 4; 0; Data analytics; Big data; Manufacturing; Cyber-physical system; Internet of things; Cloud computing; Digital twin; 5G; Blockchain; BIG DATA; SYSTEM; IMPLEMENTATION; BLOCKCHAIN; PATTERNS; CONTEXT; FUTURE; MODEL;
D O I
10.1007/s10796-021-10190-0
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Industry 4.0 is the fourth industrial revolution for decentralized production through shared facilities to achieve on-demand manufacturing and resource efficiency. It evolves from Industry 3.0 which focuses on routine operation. Data analytics is the set of techniques focus on gain actionable insight to make smart decisions from a massive amount of data. As the performance of routine operation can be improved by smart decisions and smart decisions need the support from routine operation to collect relevant data, there is an increasing amount of research effort in the merge between Industry 4.0 and data analytics. To better understand current research efforts, hot topics, and tending topics on this critical intersection, the basic concepts in Industry 4.0 and data analytics are introduced first. Then the merge between them is decomposed into three components: industry sectors, cyber-physical systems, and analytic methods. Joint research efforts on different intersections with different components are studied and discussed. Finally, a systematic literature review on the interaction between Industry 4.0 and data analytics is conducted to understand the existing research focus and trend.
引用
收藏
页码:2287 / 2303
页数:17
相关论文
共 50 条
  • [1] A Review of Research Relevant to the Emerging Industry Trends: Industry 4.0, IoT, Blockchain, and Business Analytics
    Zhang, Caiming
    Chen, Yong
    JOURNAL OF INDUSTRIAL INTEGRATION AND MANAGEMENT-INNOVATION AND ENTREPRENEURSHIP, 2020, 5 (01): : 165 - 180
  • [2] Big data/analytics platform for Industry 4.0 implementation in advanced manufacturing context
    Bonnard, Renan
    Arantes, Marcio Da Silva
    Lorbieski, Rodolfo
    Maciel Vieira, Kleber Magno
    Nunes, Marcelo Canzian
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2021, 117 (5-6): : 1959 - 1973
  • [3] Analytics in Industry 4.0: Investigating the Challenges of Unstructured Data
    Moehring, Michael
    Keller, Barbara
    Schmidt, Rainer
    Schoenitz, Fabian
    Mohr, Frederik
    Scheuerle, Max
    PERSPECTIVES IN BUSINESS INFORMATICS RESEARCH, BIR 2022, 2022, 462 : 113 - 125
  • [4] Survey on technologies present in industry 4.0
    Rozo-Garcia, Florelva
    UIS INGENIERIAS, 2020, 19 (02): : 177 - 191
  • [5] The Current Status and Developing Trends of Industry 4.0: a Review
    Lu, Yang
    INFORMATION SYSTEMS FRONTIERS, 2021, 27 (1) : 215 - 234
  • [6] A Big Data Analytics Architecture for Industry 4.0
    Santos, Maribel Yasmina
    Oliveira e Sa, Jorge
    Costa, Carlos
    Galvao, Joao
    Andrade, Carina
    Martinho, Bruno
    Lima, Francisca Vale
    Costa, Eduarda
    RECENT ADVANCES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2, 2017, 570 : 175 - 184
  • [7] Collaborative Data Analytics for Industry 4.0: Challenges, Opportunities and Models
    Lazarova-Molnar, Sanja
    Mohamed, Nader
    Al-Jaroodi, Jameela
    2018 SIXTH INTERNATIONAL CONFERENCE ON ENTERPRISE SYSTEMS (ES 2018), 2018, : 100 - 107
  • [8] A Survey on Information and Communication Technologies for Industry 4.0: State-of-the-Art, Taxonomies, Perspectives, and Challenges
    Aceto, Giuseppe
    Persico, Valerio
    Pescape, Antonio
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2019, 21 (04): : 3467 - 3501
  • [9] Link between Industry 4.0 and green supply chain management: Evidence from the automotive industry
    Ghadge, Abhijeet
    Mogale, D. G.
    Bourlakis, Michael
    Maiyar, Lohithaksha M.
    Moradlou, Hamid
    COMPUTERS & INDUSTRIAL ENGINEERING, 2022, 169
  • [10] Data Analytics and BI Framework based on Collective Intelligence and the Industry 4.0
    Lopez, Cindy-Pamela
    Segura, Marco
    Santorum, Marco
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND SYSTEMS (ICISS 2019), 2019, : 93 - 98