© Photo hramovnick - Fotolia.com
Self-learning Condition Monitoring
For a company to operate cost-efficiently, it is essential to optimize the availability of plant and machinery. This is where condition monitoring systems (CMS) can help. Predictive condition monitoring delivers reliable data enabling the early identification of wear in components such as motors, pumps and bearings. Fraunhofer IIS/EAS utilizes this approach for a smart, autonomous monitoring solution for machine components. This easy-to-use solution can be implemented rapidly and saves costs by reducing maintenance time and effort.