Predictive Maintenance of Machines

Failure of critical machine parts can lead to expensive and time consuming downtime of the production. Replacement of these parts is time consuming, and additionally the parts as well as the mechanic have to be available. Predicting the imminent failure of critical parts can lead to a planned maintenance and replacement, such that the production is not affected.

Machine Learning models can be used to predict the imminent failure of machine parts based on previous and actual runtime data of the machine. This way machine downtime can be reduced significantly.

Modulos enables domain experts such as production engineers to utilize Machine Learning in their analysis. More challenging correlations between the machine behaviour and the health of all machine parts can be found with the use of ML. By automating the process of feature extraction, hyperparameter tuning and model selection the Modulos AutoML platform gives you the opportunity to find the right algorithm for your use case, without the need of ML experts in your company.