How important is it for each row of data to have the same number of features?
A lot of blank values in row isn't a problem, you can use sparse matrices. 

I suppose you have a dataset to work with. So you can use validation and check some your suspicions. For example: fit model using dataset with &lt;40 components and test it on another part of data. 

Trying to consider order of components within device is challenging task. Maybe you can add pairs of components as features... 

This is just my suggestions, I'm not an experienced data scientist =)