Siemens has launched a new hardware platform for edge applications at the 2018 Nuremberg International Electrical Automation Systems and Components Fair (SPS IPC). As part of the Siemens Industrial Edge concept, the compact Simatic edge device is based on the Simatic IPC227E,
Siemens has launched a new hardware platform for edge applications at the 2018 Nuremberg International Electrical Automation Systems and Components Fair (SPS IPC). As part of the Siemens Industrial Edge concept, the compact Simatic edge device is based on the Simatic IPC227E, an embedded industrial computer that seamlessly connects the device layer to the automation layer, enabling direct reading and processing of production data at the production end. When the framework conditions underlying industrial applications change, applications on edge devices can adjust synchronously to keep device functionality updated in real time. With an all-metal enclosure, Simatic IPC227E delivers flexible, maintenance-free industrial performance even in the most demanding environments, and edge software is pre-installed to ensure quick commissioning.
News Photo _ Siemens introduces Simatic IPC227E, a hardware device for edge applications
Siemens Industrial edge Computing
Siemens Industrial Edge helps customers close the gap between traditional on-premises data processing and cloud-based data processing to meet individual needs. Edge computing enables real-time local feedback-free processing of large amounts of data. Industrial edge computing can also help users reduce data storage and transmission costs, as large amounts of data can be pre-processed and only highly relevant data can be uploaded to the cloud or the company's own IT infrastructure. Siemens Industrial Edge Computing supports the cloud transport protocol of MindSphere, Siemens' open cloud-based iot operating system. In the future, it will also support the Message Queue Telemetry Transfer (MQTT) protocol to further ensure flexible data exchange with other systems and cloud platforms.
Siemenzi Amberg Electronics Manufacturing plant uses edge computing to achieve energy saving and efficiency
Siemenzi Amberg Electronics Manufacturing Plant (EWA) uses printed circuit board (PCB) cutting machines to produce the Simatic series. During the milling operation, fine milling dust is produced, which has a great impact on the machine. This may cause the main shaft bearing of the equipment to get stuck, which in turn can lead to unplanned machine shutdown. To prevent this from happening, the Amberg plant uses edge computing devices to analyze the data collected by the sensors, and uses artificial intelligence to analyze the operating parameters of the machines to detect any anomalies in the spindle behavior and monitor the possibility of future failures. Machine learning algorithms are used to calculate outliers in real time, and higher than a predetermined threshold indicates that the machine is about to fail. This edge application predicts bearing corrosion and machine downtime 12 to 36 hours before an actual failure occurs. In the event of an anomaly, the time to replace the spindle of the machine tool can be planned in advance to avoid high losses caused by unexpected downtime.
When analyzing production data with cloud-based solutions, manufacturers are faced with the dual challenge of managing their core tasks while seeking efficient and cost-effective solutions for related processes such as update processing and IT security. There are many ways to collect and analyze data and use the results to optimize processes. Because of the high cost of software updates, many people are abandoning the traditional way of local data processing and opting for the digital path, that is, using the Internet's central IT infrastructure (server farms) to process and analyze data in the cloud. It supports the installation of updates on all servers through a central cloud management system, thus greatly simplifying tasks such as updating and managing applications.
At the same time as the application of cloud computing is becoming more and more mature, edge computing as a reasonable supplement to it is also developing. These complementary systems enable decentralized or centralized processing of production data. Function, intelligence, and data are no longer just happening on centralized servers in the cloud, but can also be chosen to happen at the field level, near the data source, in automation technologies at the production end. Siemens Industrial Edge Computing solutions are based on Siemens' proven hardware and software portfolio and the mechanisms used in cloud technologies, integrating the benefits of both on-premises and cloud-based data processing.
