Optimize Equipment with Data-Driven Analytics

The benefits of routine maintenance in industrial settings are often overlooked, as even well-planned programs can lead to more downtime than necessary. To improve equipment effectiveness, organizations use measures like Overall Equipment Effectiveness (OEE), which takes into account factors such as performance speed and availability. A shift from preventive to predictive maintenance has proven valuable, utilizing machine and product data to determine when maintenance is required before a problem or breakdown occurs. This approach is made possible by advanced analytics and modeling platforms that rely on time series data, such as InfluxDB, which can be used to analyze machine sensors and predict potential failures. By leveraging these tools, organizations like a German welding shop and an engine head manufacturing plant have seen significant improvements in their quality assurance processes, reduced production costs, and increased efficiency.

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