The phrase "garbage in, garbage out" has been used for decades, but it has new weight in manufacturing AI. An AI model used for predictive maintenance, quality analysis, or process optimization relies on data from machines,…
AI already produces summaries, recommendations, and reports across manufacturing. Few manufacturers trust those outputs enough to act on them. Searching a document library or summarizing a maintenance file is a support function. Recommending a process change,…
Industrial environments have been built one use case at a time, leaving most large manufacturers with fragmented IT and OT infrastructure. A manufacturer with 10 sites might run four different home-grown MES platforms, three different ERPs,…
Close to 80% of power generation deployments in ABB's global electrification and power install base run on-premise at the edge. That figure, shared by Cody Falcon of ABB Energy Industries during IIoT World Energy Day 2026,…
In manufacturing, the window between a small deviation and a costly event can be measured in seconds. A vibration pattern shifts, a batch parameter drifts, a temperature moves outside its normal band. The data exists, but…
Manufacturing AI deployments often fail when all intelligence sits in a single layer, either pushed entirely to the cloud or crammed into the sensor level. Intelligence needs to sit where it can operate reliably, respond in…
The industrial sector is flooded with claims about fully autonomous operations, but for manufacturing executives, separating marketing from operational reality is critical. Despite the billions projected for artificial intelligence this year, the factory floor remains a…
Predictive maintenance (PdM) delivers measurable returns, but building a credible ROI case requires more than vendor estimates. IIoT World created this executive guide to help plant leaders, operations directors, and CFOs quantify the financial impact of…
Manufacturers are investing in AI to improve maintenance, quality, production visibility, asset performance, and decision-making. Most of these use cases pull data from sensors, historians, machines, SCADA systems, MES platforms, engineering workstations, and other operational sources.…
I've been involved in distributed and embedded computing for about 30 years now, and one of the things I see again and again in the energy sector is how a successful AI pilot fails to become…
Most industrial AI systems on the factory floor are limited to monitoring: they read sensor data, populate dashboards, and trigger alerts without ever sending an instruction back to the machine. Coreflux, a company based in Porto,…
For decades, the promise of the digital factory was simple: more data equals more efficiency. Yet, as discussed at the ARC Industry Leadership Forum 2026, many manufacturers find themselves trapped in a productivity paradox. Despite having…