Automation is a form of technology that mechanizes a repetitive process, thereby reducing the need for human assistance. Today, thanks to innovative technology, automation can describe anything from self-checkout lanes at the grocery store to automated teller machines (ATMs) at the bank. Seeping into every industry today, automation technology is disrupting the traditional way things are done for most organizations, and the manufacturing industry is no exception.
The shift towards self-reliant IoT sensors is expected to drive the growth of industrial automation, as transforming conventional production facilities involves implementing automated systems for asset and workforce management and production processes. However, the manufacturing industry is already fairly deep into the process of leveraging automation technology; as according to “Industrial Automation Market,” the current market for automated manufacturing was at $164.2 billion in 2020 and expected to grow at a CAGR of 9.3% from 2020 to 2027 to reach $306.2 billion by 2027.
It’s no surprise that the automated manufacturing industry is rapidly growing, as the adoption of the technology holds a myriad of potential for every part of the manufacturing process. From digital twins on the factory floor to efficient new forms of supply chain processes, new industrial automation technology has the ability to truly disrupt manufacturing for the better.
Recently, Siemens, a technology company focused on industry, infrastructure, mobility, and healthcare, announced it is expanding its Industrial Edge offering for machine tools with two new edge devices. In addition to the already available IPC227E, there is now the IPC127E, an entry-level device, and the IPC427E, a powerful edge device for machine tools.
The IPC127E serves as an entry-level solution to provide connectivity and performance for simple use cases, while with the IPC427E, Siemens is launching a device with sufficient computing power to meet the demands of AI-based edge applications and sophisticated data analytics. The new Simatic ET200 adapter also offers the possibility of connecting additional external sensors and acquiring their data at a sampling rate of up to 10kHz.
For this purpose, the already known edge application Analyze MyWorkpiece /Monitor has received an update. Analyze MyWorkpiece /Monitor is used for automatic quality assurance of the machining process of a workpiece. In addition to data on the workpiece, tool, and tool path, this app can now also record data from external sensors in high temporal resolution. As a novelty, the app can also stream process data via MQTT to an external MQTT endpoint. In addition, users can visualize the workpiece of a 5-axis machining operation with the newly developed online coordinate transformation from the machine coordinate system to the workpiece coordinate system.
All other recorded data can subsequently be visualized and analyzed with Analyze MyWorkpiece /Toolpath. The insights gained enable optimization of the CAD/CAM model and the generated NC program. In addition, Analyze MyWorkpiece /Toolpath now allows the creation of realistic surface reconstruction using process data recorded with Industrial Edge for Machine Tools. This allows the workpiece quality to be evaluated before a workpiece has even been manufactured because the surface reconstruction also works with process data from an air cut.
With the release of the new version of Analyze MyWorkpiece /Monitor, users have another update of an edge app in the field of quality monitoring. From now on, all the necessary measures are stored in a single app. This includes the recording of reference data, the training of monitoring models, and the realization of process monitoring. With Analyze MyWorkpiece /Monitor, users can reduce quality assurance costs.
Overall, Siemens’ expansion signifies another step forward for industrial automation, only emphasizing technology’s place in manufacturing and on the factory floor. And as the world becomes more digital with every passing day, soon, all machine builders and users will flexibly take advantage of data processing via edge or cloud computing as needed.