Digital twin technology for sustainable industrial operations
Department of Industrial Engineering, Texas A&M University, Texas.
Review Article
World Journal of Advanced Research and Reviews, 2024, 22(02), 2347-2353
Publication history:
Received on 25 March 2024; revised on 14 May 2024; accepted on 17 May 2024
Abstract:
Digital Twin Technology (DTT) is revolutionizing the industrial landscape by enabling real-time virtual representations of physical systems. As industries pursue sustainability goals, the integration of digital twins into smart factories presents a transformative solution for enhancing energy efficiency, minimizing waste reduction, and optimizing lifecycle management. This article explores the foundational principles of DTT, its implementation in industrial automation, and its role in advancing sustainable manufacturing. Through an analysis of Industry 4.0 applications, predictive maintenance, and IoT-enabled systems, we highlight how digital twin solutions improve operational efficiency and resource optimization. By examining case studies and emerging technologies, this study demonstrates how DTT drives the transition toward intelligent factories, circular economy practices, and eco-conscious production. The findings underscore the potential of AI-driven simulations, cyber-physical systems, and data-driven decision-making in shaping the future of green manufacturing and industrial sustainability.
Keywords:
Smart Factories; Predictive Maintenance; Sustainable Manufacturing; Cyber-Physical Systems; Circular Economy; AI-Driven Simulations
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0