Amazon Web Services Recently Launched AWS IoT TwinMaker

There are no up-front commitments or fees to use AWS IoT TwinMaker, and customers only pay for the AWS services used.

Industrial companies collect and process vast troves of data about their equipment and facilities from sources like equipment sensors, video cameras, and business applications such as enterprise resource planning systems or project management systems. Many customers want to combine these data sources to create a virtual representation of their physical systems (digital twin) to help them simulate and optimize operational performance.Building and managing digital twins is hard even for the most technically advanced organizations.

To build digital twins, customers must manually connect different types of data from diverse sources (e.g. time-series sensor data from equipment, video feeds from cameras, maintenance records from business applications, etc.). Then customers have to create a knowledge graph that provides common access to all the connected data and maps the relationships between the data sources to the physical environment. To complete the digital twin, customers have to build a 3D virtual representation of their physical systems (e.g. factories, equipment, production lines, etc.) and overlay the real-world data on to the 3D visualization.

Once they have a virtual representation of their real-world systems with real-time data, customers can build applications for plant operators and maintenance engineers that can leverage machine learning and analytics to extract business insights about the real-time operational performance of their physical systems. Because of the work required, the vast majority of organizations are unable to use digital twins to improve their operations. AWS IoT TwinMaker makes it significantly faster and easier to create digital twins of real-world systems. Using AWS IoT TwinMaker, developers can quickly get started building digital twins of devices, equipment, and processes by connecting AWS IoT TwinMaker to data sources like equipment sensors, video feeds, and business applications.

AWS IoT TwinMaker automatically creates a knowledge graph that combines and understands the relationships of the connected data sources, so it can update the digital twin with real-time information from the system being modelled. Customers can import existing 3D models (e.g. CAD and BIM files, point cloud scans, etc.), directly into AWS IoT TwinMaker to easily create 3D visualizations of the physical systems and overlay the data from the knowledge graph on to the 3D visualizations to create the digital twin. Once the digital twin has been created, developers can use an AWS IoT TwinMaker plugin for Amazon Managed Grafana to create a web-based application that displays the digital twin on the devices plant operators and maintenance engineers use to monitor and inspect facilities and industrial systems.

“Customers are excited about the opportunity to use digital twins to improve their operations and processes, but the work involved in creating a digital twin and custom applications for different use cases is complicated, expensive, and prohibitive for most,” said Michael MacKenzie, General Manager, AWS IoT. “AWS IoT TwinMaker includes the built-in capabilities most customers need for their digital twins, such as connecting to data across disparate sources, modeling physical environments, and visualization of data with spatial context. With today’s launch of AWS IoT TwinMaker, more customers can now have a holistic view of their industrial equipment, facilities, and processes to monitor and optimize all of their operations in real time.”

For more information: aws.com/iot-twinmaker
Source_https://metrology.news/iot-twinmaker-creates-digital-twins-of-factories-equipment-and-production-lines/