Posted by automation_eng_77 | 4 days ago

Our plant is looking to add some predictive maintenance capabilities to our existing AB ControlLogix setup and management is pushing hard for "AI integration" but I'm honestly not sure where to even begin. We've got about 15 CompactLogix and ControlLogix PLCs running various production lines with data going to FactoryTalk View SE for HMI. Has anyone successfully integrated machine learning or AI models with Rockwell hardware? I'm trying to figure out if we need to rip out our existing infrastructure or if there's a way to layer AI on top of what we already have. Budget is decent but I need to show ROI within 18 months or this project dies.

Reply by IndustrialIoT_Sam | 3 days ago

Don't overthink this - you definitely don't need to replace your existing AB infrastructure, that would be insane cost-wise. What we did at our facility was set up an edge gateway (we used a Kepware ThingWorx setup but there's cheaper options) to pull data from the PLCs via Ethernet/IP and then push it to our cloud platform where the actual AI models run. Your ControlLogix controllers already have the data you need, you just need to get it out and into a format that Python or whatever ML framework can digest. The key is making sure you're collecting the right sensor data - vibration, temperature, current draw, cycle times, etc. We started small with just one production line and expanded from there once we proved it worked.

Reply by RockwellTech_Nina | 3 days ago

Sam's on the right track but I'd also look at FactoryTalk Analytics from Rockwell directly if you want something more plug-and-play. It's not cheap but it's designed specifically for this use case and integrates natively with your existing ControlLogix setup without needing a bunch of middleware. We implemented it last year for anomaly detection on our CNC machines and honestly the setup was way easier than I expected - most of the work was figuring out which tags to monitor and tuning the models. The other route is going open source with Node-RED or Python pulling data via pylogix library which talks directly to AB PLCs over Ethernet. That's what I do for side projects at home and it works surprisingly well, but for production environment you might want vendor support.

Reply by automation_eng_77 | 2 days ago

Thanks both - the edge gateway approach makes a lot of sense, I was worried we'd have to do something crazy with the PLC code itself. Nina I've heard mixed things about FactoryTalk Analytics, is the licensing per PLC or per tag? Our Rockwell rep keeps dodging that question lol. I like the idea of starting with open source to prove the concept before spending big money. Has anyone used OPC UA as the middleware instead of Ethernet/IP direct? I'm thinking that might be more flexible long-term if we want to add non-AB devices later since we've got some Siemens stuff in the warehouse.

Reply by IndustrialIoT_Sam | 2 days ago

OPC UA is definitely the way to go for future-proofing, you're spot on with that thinking. We actually switched to OPC UA after our initial Ethernet/IP setup because we acquired another plant that had mixed vendors and it was a nightmare managing different protocols. Matrikon or Kepware both have solid OPC UA servers that work great with AB PLCs and they can aggregate data from basically any industrial device. For the AI side, once you've got data flowing you can use Azure ML, AWS SageMaker, or even just scikit-learn on a local server - the hard part isn't the AI itself, it's getting clean, consistent data and knowing what failure modes you're actually trying to predict. Don't let your management get caught up in the AI hype, focus on solving specific problems like "predict bearing failures 2 weeks in advance" not vague stuff like "make our factory smarter" lol.

Reply by PLCguru_retired | 1 day ago

One thing nobody's mentioned yet - make absolutely sure your network infrastructure can handle the additional traffic before you start pumping data out of those PLCs. I've seen plants bring their entire control network to its knees because some eager engineer started polling every tag at 100ms intervals for their AI project. Put your data collection on a separate VLAN or use a dual-NIC setup on the PLCs if possible. Also document everything you're doing because when something breaks at 2am and you're on vacation, the poor tech on call needs to know what's talking to the PLCs and why. Been there, done that, got the angry phone calls to prove it haha.