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Intelligent production with DXQ – analytics and AI in the automotive industry
Dürr is setting new standards in data analysis and artificial intelligence with its DXQanalyze product family. These innovative solutions make it possible to analyze large amounts of data in a very short time and gain previously unknown insights – from the body shop and robotics in the paint shop to final assembly.
The use of analytics and artificial intelligence (AI) in production opens up a wide range of opportunities for automotive manufacturers to increase sustainability, efficiency, and quality in paint shops and final assembly lines. With its DXQ products, Dürr offers a continuous data pipeline—from high-resolution machine data to plant-wide production information, including digital twins in the automotive industry. This transforms big data into smart data that optimizes the entire manufacturing process. Two examples from the paint shop and final assembly can now be found at the bottom of this page.
Advantages of DXQanalyze in the paint shop
The software solutions enable real-time monitoring of process parameters in order to detect anomalies at an early stage and minimize unplanned downtime. DXQanalyze covers various areas, from process engineering to application engineering. The integration of predictive maintenance improves overall equipment effectiveness (OEE) and reduces maintenance costs. At a higher level, DXQ solutions aggregate data to draw conclusions about individual production steps and product quality. This structured error analysis as part of quality assurance in the automotive industry improves the first-pass yield and supports sustainable, efficient production.
Advantages of DXQanalyze in final assembly
In end-of-line testing, DXQanalyze reduces rework times by detecting recurring errors and supporting a closed quality loop. Automatically determined correction values can be transferred centrally to the assembly system—for greater adjustment accuracy, process stability, and product quality.
In filling technology, DXQanalyze enables precise monitoring of filling processes and detects deviations at an early stage. The analysis of historical and current data supports predictive maintenance, increases plant availability, and ensures consistently high product quality.
