This paper introduces a novel framework for developing digital twins in manufacturing, focusing on the integration of real-time data monitoring and management tools. Unlike existing approaches, this framework emphasizes the enhancement of standardization, security, and visualization to maximize operational efficiency. By addressing the limitations of current digital twin models, a comprehensive solution that leverages advanced robotic technologies and IoT to simulate and optimize modern industrial environments, has been proposed. The unique value of this approach lies in its ability to provide global and instant visibility, enabling smooth synchronization, improved resource management, and the transformation of manufacturing processes into Industry 5.0 standards.

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Towards Sustainable Digital Transformation in SMEs: Integrating IoT, Digital Twins, and AI for Enhanced Manufacturing Efficiency

  • Zeina Elrawashdeh,
  • Paul-Eric Dossou,
  • Boriska Mbilongo

摘要

This paper introduces a novel framework for developing digital twins in manufacturing, focusing on the integration of real-time data monitoring and management tools. Unlike existing approaches, this framework emphasizes the enhancement of standardization, security, and visualization to maximize operational efficiency. By addressing the limitations of current digital twin models, a comprehensive solution that leverages advanced robotic technologies and IoT to simulate and optimize modern industrial environments, has been proposed. The unique value of this approach lies in its ability to provide global and instant visibility, enabling smooth synchronization, improved resource management, and the transformation of manufacturing processes into Industry 5.0 standards.