Digital Twins in Sustainable Manufacturing: Real-Time Monitoring for Reduced Environmental Impact

Abstract

Digital twins have emerged as a transformative technology in the realm of sustainable manufacturing, offering innovative solutions for real-time monitoring and optimization of manufacturing processes. This paper explores the application of digital twin technology in enhancing sustainability within manufacturing operations by providing an interactive virtual representation of physical assets, processes, and systems. By leveraging data analytics, artificial intelligence, and the Internet of Things (IoT), digital twins enable manufacturers to monitor real-time performance, predict maintenance needs, and optimize resource consumption. This capability significantly contributes to minimizing waste, reducing energy consumption, and enhancing overall environmental performance. The study highlights several case studies demonstrating the successful implementation of digital twins across various manufacturing sectors, showcasing their potential to drive sustainability initiatives. Furthermore, the paper discusses the challenges and limitations associated with integrating digital twin technology into existing manufacturing frameworks, such as data security concerns and the need for skilled personnel. Recommendations for future research are provided, emphasizing the importance of developing standardized frameworks and protocols for digital twin integration. Overall, this paper underscores the pivotal role of digital twins in facilitating sustainable manufacturing practices and contributing to the global effort of reducing the environmental footprint of industrial operations.