Two worlds come together in the smart factory: For automation experts, the priority is stable plant operation. Meanwhile, highly flexible manufacturing calls for extensive data analyses to coordinate production processes with each other. Industrial Edge brings these two worlds together – and eliminates the need for Hollywood-style climbing frames in industrial facilities.
You might be wondering what climbing and Industrial Edge have to do with each other. The answer is simple: In my previous position as a production planner at Siemens, I wanted to install a system in a high-bay warehouse to predict outages by saving and analyzing parameters from the automation system. But where should we place the PC that would perform all the calculations? Nothing really worked: It had to be mounted on the moving transport skid, which travels back and forth between two rows of shelves eight meters high and 15 meters long. That meant we had to shut the plant down multiple times, and we had no option but to climb onto the vehicle and connect the hardware there.
What an effort! But similar situations come up in many companies that want to use data science and artificial intelligence to gather valuable information from their process data. Until now, automation and data analysis have been worlds apart. But it no longer has to be that way because Industrial Edge now provides a bridge between these two areas. Let me explain how it works.
Process data right in the PLC
Let’s go back to our initial example. Back then, to perform data analyses using high-level languages like Python, I had to install a PC because the existing automation hardware wasn’t capable of processing high-level language-based program code. That’s now a thing of the past: Our Industrial Edge portfolio includes PLCs that can run apps in high-level languages in parallel with the automation kernel (for example, an HMI panel with an additional Linux kernel). This involves transmitting process data through pipelines from the controller to the high-level language applications. And conversely, in the future it’ll also be possible to feed commands back to the plant controller. In this situation, the automation system and applications each use different CPU cores.
In other words: If you want to use process data for analyses in your system, you no longer need a separate PC or server. Everything is done locally, right in the automation system. And there’s no more climbing. Our devices already come with everything included. That’s the first point favoring using Industrial Edge.
Easily install new applications
There are still two more arguments I’d like to share with you. The first is that the system is open. New functions and features are easy to integrate into an existing system using container technology. A container is a piece of software, containing own customized functionality and standardized connectivity with runtime reliability in a host system. Even this isn’t a given: I can still remember a project for which a research partner had written a brilliant algorithm to detect upcoming downtimes in a logistics system. We were full of anticipation when we went to test it on the real system – until we realized it was impossible to install the software onto a computer from the USB stick. It would have been child’s play with an Industrial Edge device.
Manage all devices from one point
The third reason for using Industrial Edge: System management is easy and centralized. Operating system updates or new functions can simply be installed onto the devices via the network. Have you ever tried equipping two dozen systems with additional hardware and assigning the correct IP address to every new device? Believe me, it’s something you can spend a whole day on. But thanks to Industrial Edge, you can make much more practical use of your time because the central management cockpit lets you assign IP addresses conveniently using device names.
I’m sure more and more companies in the future will want to use smart systems to analyze the process data they generate, so they can run their systems with maximum efficiency. Or would you prefer not to know where you can save energy, or how you can optimize clock time? And isn’t predictive maintenance something your company is interested in?
Let me know what you’re up to with these topics and comment on my post!