Predictive Maintenance

Increasing reliability with eoda | predictive maintenance

International competition, shorter product life cycles and faster technological leaps forward – these are only a few of the challenges the production of a company is facing in the 21st century. In order to survive in an environment like this, a resource-efficient and secure planning of production processes is necessary to guarantee a consistent and high quality output. Unforeseeable machine failures as well as performance drops or deterioration in quality because of defective system components can lead to shortness of supplies which will eventually weaken the market position of the entire organization.

To meet these requirements, organizations are increasingly focusing on the improvement of maintenance, repair and operations of their machinery. In previous years, the industry shifted their focus away from only reactive repair mechanisms towards the predictive coordination of machine maintenance.

Predictive maintenance belongs to the category of the future of maintenance developments. Originally developed in the course of the “Industrie 4.0” high-tech strategy of the German government, today predictive maintenance represents the informatization of production processes - intelligent IT-based production systems on the path towards a Smart Factory. Through the generation and analysis of different machine data, the predictive power of the state of industrial plants is not only enhanced, but also provides the basis for an improved planning certainty as well as the efficient planning of repair and maintenance work.

Data Science Environment

Within the framework of the eoda | Data Science Environment, we provide you with applications for condition monitoring and predictive maintenance which connect analysts and specialty departments - user-friendly, flexible and easily integrable.


R programming language

We optimize your maintenance processes with the powerful analysis software R.



Individual methodology consulting for your objective.

Contact us

Call us on +49 561 202724-51 or send us a message:

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