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

Italo Cesidio Fantozzi (), Annalisa Santolamazza, Giancarlo Loy and Massimiliano Maria Schiraldi
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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

Future Internet, 2025, vol. 17, issue 1, 1-16

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.

Keywords: digital twin; Industry 4.0; operational excellence; Internet of Things; case study (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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