Background

In the realm of automotive manufacturing, high-pressure die-casting technology has revolutionized the production process. This strategic innovation by Tesla is leading the charge towards an electric future, where efficiency and sustainability are paramount.

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Challenge

The challenges and concerns associated with the implementation of monolithic high-pressure die-casting technology can be articulated as follows:

1. Optimization of Scrap Rate Due to New Processes: The introduction of new die-casting processes may initially lead to higher scrap rates as the production line adjusts to the intricacies of technology. This is a common challenge when adopting innovative manufacturing techniques, where the learning curve can affect product quality and consistency.
2. Aging Press Casting Equipment and Its Impact on Production Efficiency and Quality: As press casting equipment ages, there are concerns regarding its impact on production efficiency and the quality of the end product. The wear and tear on machinery can lead to variations in the casting process, potentially resulting in defects and a decrease in overall output quality

Solution/Technology

eXlens team had the experience of improving and maintaining world leading casting production lines. Quality optimization analysis and anomaly detection are core approaches to enhancing product yield and efficiency.

1. Intelligent Process Optimization Recommendation:

Providing the optimal die-casting process recipe involves leveraging vast amounts of data and models of the domain knowledge of casting process.

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2. Equipment Anomaly Detection & Alerts:

Providing  key process anomaly detection and alerts based on in-depth domain knowledge and equipment principles.

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Result

1. Yield increased by over 10%, with key failure scrap reduced by over 55%.
2. About 2-day advance alert with 95% accuracy in casting curve alerts.
3. Significant reduction in complex issue analysis time by 60%.