Multiple Fault Diagnostics in Solder Paste Printing Process Using Blind Separation Approach

Abstract

Abstract In this paper, a fault diagnosis and variation pattern identification method is presented based on blind source separation (BSS) approach which is used to extract important information from the measured data and estimate the variation pattern matrix in a solder paste printing process. BSS techniques provide the basis for identifying the precise characteristics of each individual variation pattern in order to facilitate the identification of their root causes. Measurements of mixed signals which collected from a simulated faulty process are decomposed by independent component analysis (ICA) and results from a the simulated case study show that ICA has ability to separate the original source signals from their mixtures and to identify variation pattern characteristics by using frequency domain ICA analysis. The techniques studied in this paper would benefit SMT research of correcting unidentified solder paste stenciling problems.