Anyone who is well acquainted with industrial systems will hear immediately if something is running differently than normal. This simple principle was the starting point for the development of the Bilfinger Cognitive Sensor. The digital technology supports plant operators and maintenance experts in identifying changes in the operation mode as well as faults and maintenance requirements.
In the process industry, avoiding machine downtime is the highest priority. The method often used to monitor and ensure machine health and smooth running processes are inspection rounds. However, changes in the machine condition cannot be detected efficiently all the time with regular inspection rounds as there is a chance that the change does not appear when the round is carried out or already started when no one was around. If the change is not detected early enough, reactive maintenance and production changes is the only option left which costs the company money in spare parts for the machine and revenue lost in down time.
„Sound is the most apparent sign of mechanical failure. “
Noise related machine mode detection helps significantly in maintenance and production. Using the noise to predict failure modes will decrease the reaction time significantly and improves your planning and execution of maintenance activities. With a non-invasive data recording process the sensor ensures no interruption in the normal running of the process and the decision makers get the ability to make more informed decisions which will reduce the overall risk factor in the plant. With the integration with the BCAP platform it gives the end user functionality to import and analyze data from different sources and compile them to get new insights which they previously would not have access to.