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Data Analytics in Industry 4.0: A Survey.

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Summary
This summary is machine-generated.

Industry 4.0, the fourth industrial revolution, merges with data analytics for smarter manufacturing. This research explores their intersection, identifying key topics and trends in decentralized production and resource efficiency.

Keywords:
5GBig dataBlockchainCloud computingCyber-physical systemData analyticsDigital twinIndustry 4.0Internet of thingsManufacturing

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Area of Science:

  • Industrial Engineering and Operations Research
  • Computer Science and Information Systems

Background:

  • Industry 4.0 signifies a shift towards decentralized manufacturing, emphasizing on-demand production and resource efficiency.
  • Data analytics provides techniques for extracting actionable insights from large datasets to support informed decision-making.
  • The synergy between Industry 4.0 and data analytics is crucial for enhancing operational performance and data collection.

Purpose of the Study:

  • To introduce fundamental concepts of Industry 4.0 and data analytics.
  • To deconstruct the integration of Industry 4.0 and data analytics into industry sectors, cyber-physical systems, and analytic methods.
  • To systematically review existing research and identify trends at the intersection of Industry 4.0 and data analytics.

Main Methods:

  • Introduction of core concepts in Industry 4.0 and data analytics.
  • Decomposition of the merge into three key components: industry sectors, cyber-physical systems, and analytic methods.
  • Systematic literature review to analyze research efforts and trends.

Main Results:

  • Exploration of joint research efforts across different intersections of the three components.
  • Identification of current research focus and emerging trends in the combined field.
  • Discussion of the interplay between Industry 4.0 principles and data analytics methodologies.

Conclusions:

  • The integration of Industry 4.0 and data analytics is a rapidly evolving research area.
  • Understanding this intersection is vital for advancing smart manufacturing and resource efficiency.
  • Further research is needed to fully leverage the combined potential of these fields.