In my previous blog post from early summer, I talked about IO-Link sensors with condition monitoring features that work with PLCs. I covered how condition monitoring variables can be set up as alarms and how simple logic can be set up inside the sensor so it only sets off those alarms to the PLC in real time to alert operators when something is wrong. Many companies, however, take advantage of the IoT sensor data with the long-term goal of analyzing the environmental data conditions to predict maintenance needs in real-time versus relying on a schedule. Some even want to connect directly to their MES systems to inform maintenance personnel of daily maintenance orders, which requires a separate device, such as an IoT edge gateway.
Edge gateway benefits
The biggest benefit of an IoT edge gateway is the ability to process and store large amounts of data quickly, enabling real-time applications to use that data efficiently.
An IoT edge gateway typically sits at the end or edge of your network and gathers all the sensor data either directly from the sensors or from the PLC. Since there will be a large amount of data from all the sensors on the network, part of the edge gateway setup is to filter the relevant and important information and process this vast amount of data. The edge gateway must also handle the amount of data required reliably, and it must have low latency. These important factors are often associated with the gateway’s CPU and memory specifications.
After looking at the performance of the edge gateway, comes the ‘gateway’ aspect which provides a translation to different communications networks, whether local or cloud-based. There are the hardware specs of the gateway, whether it’s using serial, USB or Ethernet for that connection, as well as the environmental ratings on the gateway. Then, more importantly, is the software side of the edge gateway. There are cloud-based communications standards designed for different applications and for either private or public cloud networks.
Edge gateways support different communications protocols, such as HTTPS, MQTT, RESTful API, C/Python API. The gateway portion also helps in the conversion of those protocols and the ease of interoperability to different platforms, such as AWS, Azure, Ignition, and Wonderware. This provides data transparency so that all the data gathered can be used across the many different software platforms.
To get to the IoT end goal, an edge gateway is necessary and it’s important to choose the correct one.
When most people think of automation in manufacturing the first thing that comes to mind is usually a robot. Without a doubt, robots play an integral part in automating the production process, and let’s face it they are pretty cool. However, there is an often overlooked topic in the automation discussion and that is Automatic Data Collection (ADC), which includes barcode and RFID technology. While it doesn’t carry the “cool factor” quite as well as robotics, RFID has helped automate manufacturing, specifically machining, over the last 30 years.
