Digital Twin

Analyzing and optimizing complex physical systems through traditional methods can be cumbersome and limited in their ability to capture timely insights. Deploying digital twin technology virtually replicates and mirrors the structure and behavior of their physical assets. Through digital twins they can get a simplified visual context of their assets (equipment, sites, products, processes) performance and related processes, saving time and operational costs related to system analysis and optimization. These digital models integrate data across IoT sensors, spatial information, and advanced analytics to provide a holistic view for customers. The AWS Digital Twin Framework provides a unified architecture spanning data collection, spatial data lakes, predictive modeling, and applications that consume and action the data. This framework enables flexible pathways to build and scale digital twin deployments across multiple business outcomes like asset performance management, product and process optimization, engineering design, site layout optimization, and an augmented workforce.