RDDS runs a test program and records the measurement data from the gear shift test so it can be repeated. With Python integration, you can automate more complex calculations with bigger data sets like the gear shift test and analyze them “in-line,” meaning right in the test sequence. In this example, shifting times and shifting quality are analyzed. The result is available directly during the test sequence and can thus be used for further testing or quality evaluation. The end customer can edit the Python script directly with the RDDS client if test criteria need to be changed or expanded.

Building on this, inline data analysis also opens up completely new testing opportunities. For example, target values can be adjusted dynamically based on the analysis results (“closed loop”) in order to intentionally drive test specimens to resonance points. More intelligent evaluation methods and automatic anomaly detection for end-of-line testing are no longer a technical obstacle thanks to the extensive Python libraries.

Python can be used to automatically process a wide variety of data formats. Even complex devices or systems with APIs beyond simple fieldbuses can be easily connected with Python. In an end-of-line test rig, for example, the measurement results (xml format) from an external structure-borne noise measurement system are automatically loaded into RDDS and parsed. The results are used for automated evaluation of the test object (pass/fail) and, at the end of the test, are uploaded to the customer's quality database together with the remaining results via a RESTful interface. The combination of RDDS and Python thus enables a fully automated and digital testing process.