A Bayesian image analysis framework for post placement quality inspection of components

A novel framework is proposed to inspect the placement quality of surface mount technology devices (SMDs), immediately after they have been placed in wet solder paste on a printed circuit board (PCB). The considered approach comprises two stages, i.e., observation and Bayesian estimation. The first stage involves the indirect measurement of each lead displacement with respect to its ideal position, centralized on its pad region. This displacement is inferred from area measurements on the raw image data of the lead region through a classification process. To increase the accuracy in the computation of the displacement, the second stage develops a combined classification/estimation process, in which the individual lead displacement classifications are viewed as measurements (or observations) of the same physical quantity i.e., the displacement of the entire component as a rigid body. Experimental results highlight the potential of the developed algorithm.