Predictive Quality

Predictive quality in the software autfactory

The 100% end-of-line test is a thing of the past. That’s because with predictive quality, we decide during production whether a part meets the quality standards – long before it reaches the final inspection. Our system uses real-time data analysis and machine learning to identify potential sources of error at an early stage and focus the inspection only on critical parts.

We ourselves are experts in the precise collection and processing of production data and work together with IconPro, a leading specialist in AI-supported analysis. By combining our strengths, we were able to create a powerful solution that takes the quality of your production to a new level.

This means less testing, fewer rejects and significantly faster production. This eliminates unnecessary rework and increases the quality of your production at the same time.

Reduction of testing times through intelligent algorithms

Our systems analyze production and testing data in real time to speed up testing processes. Through the targeted use of statistical methods and machine learning, we reduce unnecessary inspections and focus on critical areas. This reduces the testing effort and increases the throughput speed.

• Faster time to market: Reduced testing times speed up your production cycles and help launch products faster.
• Cost reduction: Less testing means shorter machine running times and lower energy consumption.
• Increased production capacity: More machine time for production thanks to optimized testing processes.
• Better use of resources: personnel deployment and test benches are planned more efficiently, avoiding bottlenecks.

Quality predictions for error-free production

With predictive quality, potential quality problems can be identified and avoided during the production process. Our AI models analyze historical and current production data to identify trends at an early stage and eliminate sources of error. This minimizes waste, avoids costly reworking and increases the overall quality of your production.

• Early error detection: Problems are identified and prevented in advance.
• Fewer rejects: Production errors can be eliminated at an early stage, which saves material costs.
• Stable processes: AI-based predictions help to minimize fluctuations in the production process.
• Less rework: By avoiding errors, there is no need for corrective measures.