In the semiconductor manufacturing industry for automotive, parts are tested at each manufacturing step to screen likely-to-fail parts. The further upstream the weak parts are scrapped, the lower the scrapping cost will be. But testing has a cost as well. A recent project at NXP sought to avoid a manual defect classification of the defects observed at the wafer inspection level. Defects are now classified as killer or not-killer from a training image dataset, and a failure probability is assessed for each die. JMP® allows a further step in correlating this failure probability to electrical tests with three types of analysis. The first analysis assessed a failure probability threshold to limit the number of parts tested to limit test cost. The second analysis highlighted the tests most correlated with failure probability. The final analysis used the list of highlighted tests to adjust test limits to screen the parts with failure probability outliers. The analyses limit test costs while increasing quality.