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Autor: Max Hoffmann

Industrial Big Data: Data-Driven Process Understanding

Industrial Big Data: Data-Driven Process Understanding

Modern Information Management in Production
Thomas Thiele, Max Hoffmann, Tobias Meisen
The digital transformation led to disruptive changes in business models of leading companies. Big Data serves as one of the key enables in this area. The transfer of this concept in the production domain towards an Industrial Big Data is key challenge for producing companies. Although exemplary key projects exist, no available characterization of structural elements in Industrial Big Data Processes exists. Therefore, this article aims at presenting initial structural elements of Industrial Big Data projects based on exemplary use cases.
Industrie 4.0 Management | Volume 33 | 2017 | Edition 4 | Pages 57-60
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  • I4S+
  • Industry 4.0
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  • Artificial Intelligence
  • Functions
    • Start-up Management
    • Maintenance
    • Logistics
    • Assembly
    • Product Development
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    • Production Control
    • Process Management
    • Quality Management
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  • Tools
    • Additive Manufacturing
    • Analytics
    • Augmented Reality
    • Blockchain
    • Modularization
    • Training
    • Robotics
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    • Simulation
    • Software
  • Management
    • Services
    • Dynamics
    • Energy Efficiency
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    • Business Models
    • Innovation
    • SME
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    • Product Piracy
    • Resource Efficiency
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