In production processes, frequently recurring faults can occur. The circumstances and consequences appear comparable, but the cause remains unclear. Countless influences affect process stability – they make a manual analysis comparable to searching for a needle in a haystack. In contrast, modern predictive maintenance procedures can analyze long histories and all influences simultaneously and identify common influences.
elimination of unplanned downtime
- Development of a model based on the best possible process behaviour
- Comparison and analysis of fleets possible
- Search for conspicuous behavior patterns
- Iterative improvement of the model by our experts
- Data exchange via different data formats possible
- Your existing sensors and measurements serve as a basis
- Access to results via cloud portal
- Results are analyzed and compiled together with the customer
- Based on the findings, suitable recognition methods can be developed
- Results can be visualized in detail in customizable dashboards
- Our international team of experts creates and maintains all mathematical models for you and advises you on all questions
- In order to achieve the best possible results, the examination is carried out in several phases. In each phase the results become clearer.
- Combination of human-machine: Feedback and expert knowledge are incorporated into the learning process in order to obtain the best possible model.
- Algorithms can be provided in common programming languages
- Integration into our predictive maintenance solution possible
When our experts analyze the data, expert knowledge is built into the modeling to achieve a goal-oriented root cause analysis. The AI models reflect the behavior of all processes, so that deviations and irregularities become evident in case of malfunctions.
Louis von Beaulieu
Phone: +49 160 90839756