AI in Manufacturing is among the areas with the most measurable benefit, because the result shows up in scrap rate, downtime and consumption. There are four most common deployments. Predictive maintenance evaluates sensor data and warns of an impending fault before the machine stops. Visual quality inspection compares product images and detects defects that the human eye misses at line speed. Planning and scheduling optimisation finds the order of jobs with the least downtime. Demand prediction improves material purchasing and inventory levels. A shared condition is data availability – if the machines do not collect data or it remains locked inside the supplier's system, the first step is not AI, but making that data accessible. For quality inspection, also allow time for collecting and labelling samples.
See also: AI use case, Grant for Company Digitalisation, Return on AI investment.
