I have an electronic component whose sensors record temperature, current and voltage values of various sub-elements. These readings are taken at regular intervals of time and I organized them as records of a dataset. In addition to these features, the dataset has a column with value 1 or 0 if at that moment the component is experiencing a malfunction or not. Here is an example of the dataset structure:
My goal is to build a model that is able to predict the occurrence of a malfunction with some time advance, so I think this is a multivariate time series prediction problem.
What approaches could I use to achieve this goal? I have read that it is possible to use Recurrent Neural Networks / LSTM but I do not have an adequate GPU.