New gateway between cloud, in-company IT and production
It can be used for connecting the production process to a cloud-based analysis of machine and production data, for example. The new IOT gateway will also be equipped with remote edge functionality for easy integration into Siemens Industrial Edge solutions.
Gateway as a retrofit
The gateway can also be retrofitted in already existing plants, where it then harmonises communication between different data sources, analyses the data, and passes it on for evaluation to a cloud, for example. This cloud can be MindSphere, or any other solution preferred by the user. The Simatic IOT2050 complements the MindConnect Nano cloud gateway from Siemens. This gateway is already on the market, and is specifically designed for MindSphere.
The hardware of the new Simatic IOT2050 gateway has a compact design and is based on rugged, reliable and long-lasting industrial technology. The device is suitable for both wall and standard rail mounting, is equipped with a power-saving Texas Instruments ARM AM 6548 (+Secure Boot), 2 GB DDR4 RAM and multiple interfaces including two Gbit LAN, two USB, and a serial and Arduino interface. It comes with the Simatic Industrial OS already installed. Simatic IOT2050 can be easily expanded for tailor-made solutions with Arduino shields and mini PCIe cards. It also supports Linux based on Debian. There are also many other options for programming in high-level languages. Together with the planned edge functionality, it is easy for the user to integrate the Simatic IOT2050 into Siemens Industrial Edge solutions.
The Simatic IOT2050 is typically used for preventive machine maintenance and linking production to the ERP (Enterprise Resource Planning) level in order to minimise expensive production downtimes. Relevant indicators can be evaluated and impending signs of wear detected at an early stage.
These are the ways the new IoT Gateway contributes to making production more versatile, reliable and efficient. Simatic IOT2050 acquires, processes and stores the relevant data. These are transferred to a cloud-based analysis tool, and the evaluated data then passed back from the cloud to the production maintenance system. This continuous data exchange completes the control loop for optimising maintenance intervals in production plants.www.siemens.com