GOOD PRODUCT EVALUATION

 When we create a Good Product Model we want to test it with new samples knowing if they are good or bad. There is of course an uncertain area that we can calculate from experience we get from several evaluation.

In this Excel plot we see the values for "Max Peak T", for the training set (samples before Mars 2019) and new batches we consider are fine from Mars to June. There is a set of bad samples prepared with mixtures out of tolerance for a certain component or components of the mixture.

As we can see the model works in some cases but there are other that are misclassified, so we have to try other treatments or models to check if we can classify them better. Anyway there is always an uncertain zone and we have to check for confidence levels of the prediction.

Looking for problems in the Residual plots

Control charts or residual plots are very helpful to detect problems, and we have to look at them always to try to understand how well our model performs. It is important tp have a certain order ibn the X axis to succeed in the interpretation. In this case is in order by the value of the reference, but the order can be by date, by GH,....

 

There are different rules and we have to check  them. One rule is that there must not be nine points or more in a row on the same side of the zero line, and this is what it happens in this case for a model where the Monitor functions show that there is a problem with the slope. 

 

Look from left to right and see how more than nine points (red) in a row are over the zero line. Once corrected (yellow points) the distribution improves.