Problem
A world-leader in welding rod manufacturing company working in 3 shifts wanted to monitor vibrations of machines, measure productivity especially in 3rd shift by monitoring On/Off time, further vibration of the machine due to change in the worker and also predict the failure in advance. This deployment was different from any other predictive maintenance use cases as we had to deep dive into the data.
Solution
To overcome this issue, we have deployed Pro version of COIN on the machines to gather accelerometer sensor data in all the 3 axis, viz. axial, horizontal, and vertical directions. We run a complex algorithm on COIN wherein data from COIN is analyzed and a final output is displayed on the dashboard. Currently, we are streaming data every minute from the accelerometer and gyroscope sensor. There is an option to set threshold values for each of the sensors and get an alert only when it crosses.
With this deployment the customer gets a lot of insights on the machine vvibration, predict the failure well before it happens, and also the pattern in which machines are running.
Benefits of the system
- Overall Machine Performance Parameter monitoring
- Machine utilization report and alarm indication if idle for more than defined time slot
- Real-time data processing and online update collection at the central server
- Automated Report, Customized Analytics and dashboard and notifications of Processed Data
- Cost-effective Data transmission- 3G/LTE, multiple-sim aggregation
Expected RoIe
- Reduce losses due to unplanned shutdown
- Reduction in the replacement cost of bearing, gearbox repairs, motors etc.
- Estimate on ROI is 6 months
