Here’s something that’ll keep you up at night: that perfectly calibrated sensor feeding your SCADA system might be lying to you right now. At the recent Honeywell User Group conference, industry experts dropped a truth bomb that many of us have suspected but few want to admit – industrial automation data quality problems are often more catastrophic than equipment failures.
Claudia Chandra from Honeywell put it perfectly: while we obsess over vibration monitors and temperature sensors, the real trouble starts with corrupted, delayed, or just plain wrong data. Think about it – when a motor fails, you know immediately. But when your data starts drifting or gets stuck in transmission, you’re making production decisions based on fantasy numbers. I’ve seen plants run for weeks with “ghost” efficiency metrics that looked great on paper while actual throughput was tanking.
Edge AI: The New Sheriff in Data Town
The timing couldn’t be better for the ongoing edge AI versus cloud AI debate to intensify. Edge computing is becoming the go-to solution for industrial automation data quality issues because it processes information right where it’s generated. No more waiting for round trips to distant servers or dealing with network hiccups that corrupt your process data.
This shift is getting serious hardware backing too. Renesas just launched their R-Car X5H, the industry’s first multi-domain automotive SoC for software-defined vehicles. While that’s automotive-focused, the underlying technology – processing multiple data streams simultaneously at the edge – is exactly what manufacturing needs for real-time quality control.
Nordic’s new nRF9151 development kit is another piece of this puzzle, especially for remote assets. When your critical equipment is scattered across a facility or multiple sites, having robust cellular IoT connectivity with satellite backup means your data streams stay clean and continuous.
Building Better Infrastructure
Speaking of infrastructure, it’s refreshing to see practical solutions getting attention. AutomationDirect’s expansion of modular enclosure components might not sound sexy, but proper hardware protection is fundamental to industrial automation data quality. A sensor that gets moisture intrusion or vibration damage will feed you garbage data long before it completely fails.
The evolution in electronic prototyping is equally important. Modern simulation and modeling tools let us test data acquisition scenarios before deployment, catching potential quality issues in virtual environments rather than on the production floor.
As we head into 2026, I’m betting the companies that survive the next wave of digital transformation will be those that prioritize data integrity over data volume. What’s your experience been with stale data incidents – have you caught any lurking in your systems lately?