What is a smart factory?

A smart factory is a production site where machines, sensors and production systems share data continuously, so planning, quality and maintenance run on what is happening on the line right now instead of on yesterday's spreadsheet.

In practice that means the PLCs and SCADA on the machines, the MES that tracks orders and batches, the historian that stores sensor values and the ERP that holds orders and stock all feed one picture. AI is the layer that turns that picture into decisions: which machine will fail next week, which batch is drifting out of spec, how much to produce for next month's demand.

What makes a factory smart

Three things, in this order. Connected data: machine signals and production events are captured automatically and stored with timestamps, usually in a historian and the MES. One shared view: OEE, scrap, downtime and order status are visible per line and per shift without someone compiling them by hand. Decisions that use the data: planners, maintenance engineers and quality staff act on alerts and forecasts that come from that data. Most factories have the first, part of the second, and little of the third.

Where AI fits in a smart factory

The value usually sits in four places: predictive maintenance from vibration, temperature and current signals; visual quality inspection with cameras on the line; demand and production forecasting from ERP order history; and OEE analysis that explains why a line loses time, not only how much. Each runs on data the factory already collects, which is why the first step is checking what the MES and historian actually hold.

What you need before you start

A clear question (which losses cost the most), access to at least six to twelve months of machine and production data, and someone on the shop floor who owns the outcome. You do not need a new MES or a data platform first: most first projects read from the systems already in place and write results back to a dashboard or the MES.

How Crux Digits helps

We open up MES and historian data, build the model on your own production history and connect the result to the screens your planners and engineers already use, alongside your ICT partner and your machine suppliers. See AI for manufacturing for the use cases and how a project runs.