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Digital Twins: Strategic Guide to Utilize Digital Twins to Improve Operational Efficiency in Industry 4.0

Author

Listed:
  • Italo Cesidio Fantozzi

    (Department of Enterprise Engineering, University of Rome Tor Vergata, 00133 Rome, Italy)

  • Annalisa Santolamazza

    (Department of Enterprise Engineering, University of Rome Tor Vergata, 00133 Rome, Italy)

  • Giancarlo Loy

    (Department of Enterprise Engineering, University of Rome Tor Vergata, 00133 Rome, Italy)

  • Massimiliano Maria Schiraldi

    (Department of Enterprise Engineering, University of Rome Tor Vergata, 00133 Rome, Italy)

Abstract

The Fourth Industrial Revolution, known as Industry 4.0, has transformed the manufacturing landscape by integrating advanced digital technologies, fostering automation, interconnectivity, and data-driven decision-making. Among these innovations, Digital Twins (DTs) have emerged as a pivotal tool, enabling real-time monitoring, simulation, and optimization of production processes. This paper provides a comprehensive exploration of DT technology, offering a strategic framework for its effective implementation within Industry 4.0 environments to enhance operational efficiency. The proposed methodology integrates key enabling technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning to create accurate digital replicas of manufacturing systems. Through a detailed case study, this work demonstrates how DTs can optimize production processes, reduce downtime, and improve maintenance strategies. The findings highlight DTs’ transformative potential in achieving continuous improvement, competitiveness, and operational excellence. This research aims to provide organizations with actionable insights and a roadmap to leverage DT technology for sustainable industrial innovation.

Suggested Citation

  • Italo Cesidio Fantozzi & Annalisa Santolamazza & Giancarlo Loy & Massimiliano Maria Schiraldi, 2025. "Digital Twins: Strategic Guide to Utilize Digital Twins to Improve Operational Efficiency in Industry 4.0," Future Internet, MDPI, vol. 17(1), pages 1-16, January.
    • Handle: RePEc:gam:jftint:v:17:y:2025:i:1:p:41-:d:1569593
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