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Field of research: AI for resilience in industry

The sudden failure of components and systems in production causes massive problems and costs time and money. An early prediction of whether a component will fail is very important for operators. If the measured values are not available, sensors must be installed in the process. Installing these sensors is expensive. In many cases, there are sufficient databases of error messages from production.

Example: Customized machine learning pipeline for your reliability

In the complex production processes, certain error message patterns emerge that indicate an impending component failure. If these error message patterns of the individual components are known, the operator can react to the impending failure at an early stage.

With our AI solution, we evaluate these error patterns and monitor the extracted error messages in the error log of the components during operation. As soon as an error pattern is detected, our system alerts the operator.

Framework configuration Fail-safe

With our special configuration for reliability, you receive customized analyses and evaluations. Existing modules are supplemented with the following additional modules.

  • Error pattern detection

    1
    • Visualization of error patterns
    • Modeling of hierarchical dependencies
    • Consistency check of the data
  • Error pattern monitoring

    • Monitoring of the individual error messages
    • Continuous calculation of the reliability of components/systems
    2

    Error pattern monitoring

  • Error pattern calculation

    3
    • Specific model creation for the recognition of error patterns
    • Automatic calculation of new error patterns
  • Optimization of error patterns

    • Merging of individual error patterns
    • Calculation of fail-safes
    4

    Optimization of error patterns

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