Error detection for painting robots

With the help of log data, two concrete error patterns are modelled and a procedure for identifying the errors is developed.

Two fault patterns can be identified with very high accuracy
For the implementation, the software manufacturer has corresponding instructions available
Successful presentation of the fault detection component to the machine manufacturer


A software company is planning to expand the monitoring software of a machine manufacturer's painting robots to include a component for the early detection of faults. For the verification of the functionality of the early detection within the scope of a Proof of concepts the software producer needs functioning detection models.


Together with the data science team of the software provider, a Use Case Workshop is carried out. In the process, meaningful variables for the error patterns are determined on the basis of the log data (Feature engineering) are developed. Afterwards, classification models for the detection of error patterns and evaluation of the procedures are estimated. On this basis, the steps required for implementation are described.


The customer can demonstrate the performance of the component to his machine manufacturer using the proof of concept. The software developers have concrete instructions for the Implementation of error detection before.

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