We will explain examples of manufacturing sites such as factories.
In factories that manufacture various parts and products, it is an issue to ensure maintenance and inspection of production lines.
Until now, the mainstream was post-maintenance, in which equipment operating on the production line was replaced after it was broken, and preventive maintenance, in which equipment was replaced all at once regardless of whether the equipment was broken or not.
However, this method requires enormous maintenance costs.
If the motor control equipment of the production line or the compression equipment of the aging air conditioning equipment breaks down, the production line and air conditioning will stop completely, and as a result, production will also stop, leading to compensation for the delivery destination. There are many cases where it ends up. Therefore, maintenance is required even at high cost.
There is a booming movement to detect slight changes in the state of equipment by sensing and convert it into data to help maintain the equipment before it completely stops after a failure occurs. This is equipment predictive maintenance.
It senses the vibration, frequency, acceleration, etc. of motor control equipment and monitors the status and changes of each equipment. Also, in the case of compression equipment such as compressors, the values of temperature, pressure, current, voltage, etc. are monitored, and if any of the values changes, it may be something including a failure.
Experience, knowledge, and know-how are required to determine what kind of failure will occur when the sensing data changes.
The expectation for IoT here is primary screening.
It is very effective to easily detect signs of failure by monitoring using sensors and take measures in advance, considering the enormous loss caused by the shutdown of the production line. As a result, maintenance costs can be reduced.
With Tele-Sentient, various sensors can be connected by plug and play, making it easy to build equipment predictive maintenance applications.
If you are considering equipment predictive maintenance using IoT, please feel free to contact us.