Automated optical method for ultrasonic bond pull force estimation

An automated method to non-destructively estimate ultrasonic bond pull force is presented and validated. Scanning white light interferometry (SWLI) measures bond geometry whereas the singular value decomposition of a SWLI image extracts the characteristics of the imaged bond geometry in terms of eigenvectors. Soft modeling selects those parts of the eigenvectors that are important for predicting the highest sustainable pull force. We show that SWLI measurement, statistical feature selection and bond pull force prediction can be combined to automatically perform non-destructive bond quality monitoring. Such automation removes subjectivity as well as operator limitations and errors present in earlier approaches (Schäfer et al., 2007), since no pre-selection of bond geometry or shape is needed. The proposed method was verified by experimental measurements on 132 single-point tape automated bonds. The results show that the method predicts maximum sustainable bond pull force with a prediction accuracy comparable to that of the operator based method. The three most important features in the image of the bond predicted the maximum sustainable bond pull force with an error of 11.4%. Not having to rely on the input of an experienced operator is the major advantage of this contribution.