Adaptive Digital Twin Technology for Predictive Maintenance and Au-tonomous Decision-Making in Industrial Internet of Things Ecosystems
Keywords:
Adaptive Digital Twin, Predictive Maintenance, Industrial Internet of Things, Autonomous Decision-Making, Industry 4.0, Data-Driven AutomationAbstract
The Industrial Internet of Things (IIoT) is revolutionizing modern industries by enabling real-time monitoring, data analytics, and automation. Adaptive Digital Twin (ADT) technology enhances these capabilities by creating dynamic, self-learning models that mirror physical assets. This paper explores the integration of ADTs into IIoT environments, focusing on predictive maintenance and autonomous decision-making. The study examines past literature, highlights key methodologies, and presents case studies demonstrating the effectiveness of ADTs in optimizing industrial operations. Additionally, we provide comparative data and graphical analysis illustrating performance improvements in various industrial scenarios.
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