IoT Data Analytics Driving Digital Twin Systems for Sustainable Operations Management

Digital twin technology, which provides dynamic and real-time representations of physical assets, systems, and processes, has become a game-changing tool in operations management. Digital twins facilitate ongoing operations monitoring, simulation, and optimisation by fusing data analytics, artificial intelligence, and Internet of Things (IoT) sensors. This research investigates how real-time data analytics made possible by digital twin technologies improve operations management's sustainability. It looks at how well the technology can find inefficiencies, cut waste, and enhance resource use in a range of industrial industries. The study emphasises important advantages such supply chain transparency, energy efficiency, and predictive maintenance, all of which help to lessen an operation's environmental impact. The report also highlights how digital twins may support data-driven decision-making that supports business sustainability objectives. To illustrate real-world uses and quantifiable results, case studies from the industrial, logistics, and smart city industries are examined. The study comes to the conclusion that, by facilitating proactive and flexible management techniques, digital twin technology not only increases operational effectiveness but also promotes long-term sustainability. Integrating digital twins into operations management gives businesses a competitive edge for long-term growth and innovation as environmental regulations put more and more pressure on them to comply.