so here's my problem :
I'd like to implement a predictive maintenance program as part of a demo. I collect data from 1 machine(temperature, vibrations, uptime, etc), and I don't have any historical failure data on this machine.
So, is it possible to do some predictive maintenance with that ? The idea would be to have the following outcome : -will the machine suffer a failure in near future, or not ? -predict RUL if possible
I can run the machine to get more data, but I won't be able do create a database with historical failure.
At first, I wanted to use deep learning algorithms but I quicly realised that I don't have what's necessary for the learning part. So, can I use statistical models from machine learning to solve my problem ? If yes, which ones would work well with my problem ?
If you have any other ideas, I am open to any solution !
thank you in advance