Why does system A stop or when must component X be replaced? We combine condition monitoring with our know-how in the field of data science in order to create a comprehensive and intelligent system.
As a proven partner in the field of predictive maintenance, we not only offer you competent advice, but are also your contact for the development of analysis models. We recognize patterns in historical machine data and develop forecast models for you that help you to identify defective components before defects in the machine occur.
One platform – many possible applications
YUNA was born from the idea of simplifying predictive maintenance and creating value in companies. YUNA combines intelligent, predictive maintenance with the possibility of developing your own data projects. This allows not only to secure one’s own production, but also to increase the availability of the machines.
Take your production to the next level and develop your own personal Smart Factory 2.0.
Our methods – your advantages:
Reduce costs – expand business model
A machine breakdown causes expensive downtimes, the necessary maintenance and personnel and material costs. Predictive maintenance enables you to coordinate maintenance according to your needs, avoid unnecessary maintenance work and reduce sales losses due to production downtimes.
Use intelligent maintenance as a vehicle for new services! With intelligent maintenance systems, you not only sell machines – you also offer availability. This sets you apart from the competition and at the same time creates new sources of income.
Improvement of work processes
The continuous evaluation of the machine data enables you to gain a deeper understanding of your machines. In addition to the early detection of occurring faults, the use of data science allows you to detect operating errors or defective configurations. Thereby, operating procedures and output quality can be improved.
The unforeseen failure of an industrial plant can lead to supply bottlenecks. With predictive maintenance, you can avoid unforeseen machine failures and better align production planning with the maintenance work required.