Collecting and interpreting the available data is already a sound way of monitoring the condition of machines. This requires a deeper understanding of the machines and processes so as to generate meaningful information from the "bare" data. Analyses based on Machine Learning (ML) and AI can help identify anomalies faster.

In our webcast, we also explain the model and data-based approach to analyzing the condition of machines, or the question of where the data can be evaluated – in the controller or cloud.

We also present how the drive can become a sensor and how easy the implementation of condition monitoring can be, to obtain comprehensive information on the "state of health" of machines and systems without additional, cost-increasing sensor technology.

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