Supreme - Smart Sensoring
To reduce the down time and associated costs in a production facility, the predictability of failures is very important.
SUPREME - Smart Sensoring and Predictive Maintenance in Steel Manufacturing
This can be achieved when firstly the relevant parameters on operational conditions are monitored and secondly that data is properly processed to obtain accurate estimates of time to failure. In this project, the first challenge will be addressed by developing advanced wireless sensor networks, that enable the collection of the right data in a flexible way.
The second challenge will be addressed by the development of physical failure models for the most critical components in the system. By feeding the models with the monitored variation in operational settings, the time to failure can be predicted and appropriate maintenance tasks can be scheduled. For less critical components a more data-driven approach will be followed, resulting in a decision support tool enabling optimization of the maintenance process and maximizing plant uptime.
Looptijd: In progress
Mede-projectleiders: Prof. dr. ir. T. Tinga
Partners: Universiteit Twente, Faculteit Engineering Technology (ET), Technische Mechanica (TM)
Projectmiddelen: € 510.268
Schrijf u in voor onze nieuwsbrief en blijf op de hoogte van het laatste nieuws over Commit2data