How to anticipate production failures and improve plant response with AI

The ability to anticipate on the shop floor no longer depends only on experience or reacting quickly when an incident appears. It also depends on the ability to read the data with context, detect patterns that are not always perceptible to the naked eye, and rely on predictive models to identify anomalous behaviors before they translate into an operational problem. In demanding production environments, this way of interpreting what happens in the process has a direct influence on quality, efficiency and operational responsiveness. The analysis of the production history allows you to deepen this reading, identify anomalies, better understand certain failure behaviors and provide more visibility to daily operations. In addition, it is possible to assist the operator with data-based technical recommendations and to monitor trends and deviations to promote more proactive management, with more agile decision-making thanks to artificial intelligence.