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Knowledge Reasoning with Semantic Data for Real-Time Data Processing in Smart Factory.

Shiyong Wang1, Jiafu Wan2, Di Li3

  • 1School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510640, China. mesywang@scut.edu.cn.

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Summary
This summary is machine-generated.

This study introduces a smart factory framework using cloud computing for real-time industrial data analysis. It enables intelligent negotiation for flexible production and fault detection, enhancing manufacturing efficiency.

Keywords:
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Area of Science:

  • Industrial Engineering
  • Computer Science
  • Data Science

Background:

  • High-bandwidth networks and cloud computing generate mass data in manufacturing.
  • Industrial data analysis is crucial for monitoring, optimization, flexibility, and transparency.
  • Existing architectures are inadequate for real-time data processing in manufacturing.

Purpose of the Study:

  • Define a smart factory as a cloud-assisted, self-organized system.
  • Propose a scheme integrating knowledge reasoning with real-time semantic data.
  • Develop a benchmarking system for smart manufacturing applications.

Main Methods:

  • Defined smart factory concept with cloud supervision for fault detection.
  • Proposed integrating knowledge reasoning and semantic data processing.
  • Built a benchmarking system for a smart candy packing application.

Main Results:

  • The proposed system supports direct consumer customization and flexible hybrid production.
  • Real-time data collection and processing enable fault diagnosis and statistical analysis.
  • Demonstrated a functional smart factory benchmarking system.

Conclusions:

  • The developed framework effectively supports real-time data analysis in smart manufacturing.
  • Integrating knowledge reasoning and semantic data enhances fault detection and system optimization.
  • The smart candy packing application serves as a viable model for advanced manufacturing systems.