DIGITAL TWINS IN INDUSTRIAL IOT: APPLICATIONS IN PREDICTIVE MAINTENANCE AND OPERATIONS MANAGEMENT

Abstract

The integration of Digital Twin technology into Industrial Internet of Things (IIoT) systems is revolutionizing industries by enhancing predictive maintenance and optimizing operations management. Digital Twins are virtual replicas of physical assets or systems, which use real-time data from sensors and other IoT devices to simulate and predict the behavior of physical objects. This paper explores the transformative role of Digital Twin technology in IIoT, focusing on its applications in predictive maintenance and operations management. It provides a detailed analysis of how Digital Twins enable real-time monitoring, fault prediction, and performance optimization in industrial environments. The study also discusses the challenges associated with deploying Digital Twins, including data integration, computational costs, and scalability, and presents future directions for leveraging this technology in industrial applications. The paper concludes by emphasizing the potential of Digital Twins to enhance operational efficiency, reduce downtime, and improve decision-making in manufacturing and industrial sectors.