Enhancing Data Management in Industry 5.0: The Role of Digital Twins in Optimizing Industrial Operations

Raju Imandi, B. Chethana, B. M. Prabhu Prasad, Kamalakanta Sethi and B. N. Pavan Kumar
Additional contact information
Raju Imandi: Indian Institute of Information Technology Sri City
B. Chethana: Aptiv
B. M. Prabhu Prasad: Indian Institute of Information Technology
Kamalakanta Sethi: Indian Institute of Information Technology Sri City
B. N. Pavan Kumar: Indian Institute of Information Technology Sri City

A chapter in Industry 5.0, 2025, pp 211-236 from Springer

Abstract: Abstract Industry 5.0 heralds a transformative shift in the evolution of manufacturing dynamics, emphasizing a synergistic blend of human ingenuity with cutting-edge intelligent systems. This chapter focuses on the role of digital twins—sophisticated digital counterparts of physical entities—in revolutionizing data management and enhancing streamlined functionality leveraging real-time sensor data, digital twins accurately mirror and monitor complex industrial processes, providing a comprehensive analytical platform. These digital twins facilitate predictive maintenance and robust decision-making, significantly reducing downtime and operational costs. Furthermore, they enable effective risk management by simulating potential scenarios, allowing companies to proactively address possible challenges. Through seamless human-machine collaboration, digital twins enhance the potential for smarter, more sustainable operations, optimizing resource use and minimizing environmental impact. This chapter delves into how digital twins act as pivotal enablers within Industry 5.0, driving the redefinition of industrial operations towards more intelligent, efficient, and sustainable outcomes.

Keywords: Industry 5.0; Digital twins; Human-machine collaboration; Predictive maintenance; Sustainable operations; Real-time data; Risk management (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-87837-4_9

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DOI: 10.1007/978-3-031-87837-4_9

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