  In pick and place (P&P) process of surface mount technology (SMT) the placed
component can shift from its ideal (or designed) position on the wet solder
paste. The solder paste with some fluid properties could slump and the
unbalance between different sides of solder paste can lead to other forces on
the components as well. Though the shifts are usually considered to be
negligible and can be made up to some extent by the following self-alignment
during the process of soldering reflow, it should be attracted attention as its
importance for addressing the quality of the printed circuit board (PCB) in
SMT. To minimize or control the component shifts, whose relationship with the
characteristics of the solder paste (e.g., offset, volume) should be studied
initially. In this paper, we design a comprehensive experiment and collect the
data from a state-of-the-art SMT assembly line. Then we use support vector
regression (SVR) model to predict the component shifts based on different
situations of solder paste and placement settings. Also, two kernel functions,
linear (SVR-Linear) and radial basis function (SVR-RBF), are employed. The
achieved results indicate that the component shift in P&P process is
significant, and the SVR model is highly qualified for the forecast of the
component shifts. Particularly, the SVR-RBF model outperforms the SVR-Linear
model considering the prediction error.

Systems and Control;Systems and Control