In factories to ensure smooth operations, it’s vital to identify component failures ahead of time. Numerical analysis can help you achieve that and can prevent nasty surprises occurring, in this blog we will tell you how it’s done in numerical works.
Imagine you are having a machine in your factory and in its usual operations it emits frequencies of \(f1\) and \(f2\) of sound and that’s the normal operation, now look at the image below:
All of a sudden a frequency of \(f3\) get emitted, and frequency \(f2\) gets dropped and frequency \(f1\) which is the dominant sound continues. Now after three days of \(f3\) and two days of absence of \(f2\), there is a failure and the machinery fails to operate.
Our intelligent system learns from the failure and its observations, then from your inventory management it knows this part has been replaced, so it learns. Soon it will be able to predict which part in which machinery will fail and when it will fail, so you can replace the part in advance and can avoid loss.
So how we do it?
Every machinery emits noise and vibrations, this will be picked up by our system and converted into electronic signals. A special processor called Digital Signal Processor (DSP) will convert these signals into individual frequency components as indicated by red, green and black wavy lines above, these frequencies and their amplitudes along with time of occurrence is fed to our neural network, this along with your part replacement log / parts inventory is fed to a artificial brain which learns to correlate things and predict what will happen in the future.
If you would like to predict machine failures in your factory, you can contact us.