An outlier detection based approach for PCB testing

Capacitive Leadframe testing is an effective approach for detecting faults in printed circuit boards. Capacitance measurements, however, are affected by mechanical variations during testing and by tolerances of electrical parameters of components, making it difficult to use threshold based techniques for defect detection. A novel approach is presented for identifying boards that are likely to be outliers. Based on Principal Components Analysis (PCA), this approach treats the set of capacitance measurements of individual connectors or sockets in a holistic manner to overcome the measurement and component parameter variations inherent in test data. The effectiveness of the method is evaluated using measurements on three different boards. Enhancements to the technique to increase the resolution of the method are presented and evaluated.