Projecting bad batches over training PC space

Dear readers, along this night this blog will reach the 300.000 visits and I am happy about that. So thanks to all of you for visiting this blog.

 

Along the last posts I am writing about the idea to get a set of samples from several batches of a product which is a mixture of other products in a certain percentage. Of course the idea is to get an homogeneous product with the correct proportions of every product which takes part of the mixture.

 

Anyway there is variability in the ingredients of the mixture itself (different batches, seasons, origins, handling,..), and there are also uncertainty in the measuring of the quantities. It can be much worse if by mistake an ingredient is not added to the mixture or is confused by other.

 

So, to get a set with all the variability that can be allowed is important to determine if a product is correctly mixed or manufacturer.

 

In this plot I see a variability which I considered correct in a "Principal Component Space"

Over this PC Space we project other batches and we check if the projections falls into the limits set during the development of the PC Model. Of course it can appear new variability that we have to add to the model in a future update.

 

But to check it the model performs fine we have to test it with bad building batches, and this is the case in the next plot where we can see clear batches that are out of the limits (specially samples 1,2 and 3) with much more water than the samples in the training model.

 

We have to see the other samples much more in detail and to detect if the are wrong and the reason why.
So coming post about this matter soon.