Smart maintenance using artificial intelligence

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Preventing unplanned stoppages before they can occur is the aim of the smart analysis system being used in assembly at BMW Group Plant Regensburg. Predictive maintenance is proactive and preventive – and this is precisely what the smart monitoring system offers. Data-driven analyses of conveying equipment allows potential faults to be identified early and avoided – thereby maintaining optimal vehicle production flow. The artificial intelligence (AI)-supported system avoids an average of around 500 minutes of disruption per year in vehicle assembly at the Regensburg plant alone.

Data analysis for faster, preventive response to potential disruptions

For assembly at BMW Group Plant Regensburg, vehicles are generally attached to mobile load carriers or skid systems, which pass through the production halls in a chain. Any technical fault in the state-of-the-art conveyor systems can bring assembly lines to a standstill – requiring more maintenance effort and thus resulting in higher costs. To prevent this from happening, the innovation team at BMW Group Plant Regensburg has developed a system that can identify potential technical defects early – and thus avoid any lost production. The conveyor elements affected can be removed from the assembly line and repaired, away from production. The advantage is that the monitoring system does not require any additional sensors or hardware, but evaluates existing data from installed components and conveyor element control. An alarm sounds if anomalies are found.

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