News

AWS IoT SiteWise Edge Goes GA

• By John K. Waters
• 08/04/2021

The IoT SiteWise Edge feature of the AWS IoT SiteWise managed service, which was unveiled in preview last December, is now generally available, Amazon Web Services announced.

IoT SiteWise automates the process of collecting and organizing industrial equipment data via software running on a local gateway. The gateway connects to a facility's on-premises data servers, collects and processes data, and sends the data to the AWS cloud. It can be used to model physical assets and processes, and to compute common industrial performance metrics.

IoT SiteWise Edge is designed to enable users to collect and process equipment data on-premises for low-latency applications that must continue to work even when a connection to the cloud is unavailable. Essentially, the "Edge" feature brings the capabilities of AWS IoT SiteWise in the cloud to the users' premises.

The new feature makes it easy to collect, process and monitor equipment data locally before sending the data to AWS Cloud destinations, explained Channy Yun, principal developer advocate for developer relations at AWS, in a blog post. The software can be installed on local hardware, such as third-party industrial gateways and computers, or on AWS Outposts and AWS Snow Family compute devices. It uses AWS IoT Greengrass, an edge runtime designed to help build, deploy and manage applications.

"With AWS IoT SiteWise Edge, you can organize and process your equipment data in the on-premises SiteWise gateway using AWS IoT SiteWise asset models," Yun explained. "You can then read the equipment data locally from the gateway using the same application programming interfaces (APIs) that you use with AWS IoT SiteWise in the cloud. For example, you can compute metrics such as Overall Equipment Effectiveness (OEE) locally for use in a production-line monitoring dashboard on the factory floor."

Yun cites three use cases for IoT SiteWise Edge:

• Localized testing of products: The testing of automotive, electronics, or aerospace products might generate thousands of data points per second from multiple sensors embedded in the product and the testing equipment. Users can process data locally in the gateway for near-real-time dashboards and store just the results in the cloud to optimize their bandwidth and storage costs.
• Lean manufacturing in the smart factory: Users can compute key performance metrics such as OEE, Mean Time Between Failures (MTBF), and Mean Time to Resolution (MTTR) in the gateway and monitor local dashboards that must continue to work even if the connection of the factory to the cloud is temporarily interrupted. This ensures that factory staff can identify and identify the root cause of every bottleneck as soon as it arises.
• Improving product quality: The users' local applications can read equipment and sensor data from AWS IoT SiteWise Edge on the gateway as it is collected and combine it with data from other sources like enterprise resource planning (ERP) systems and manufacturing execution systems to help catch defect-causing conditions. The data can be further processed through machine learning models to identify anomalies that are used to trigger alerts for staff on the factory floor.

Yun offers details about getting started using this feature in his blog post. AWS IoT SiteWise Edge is available in all AWS Regions where AWS IoT SiteWise is available, the company says.