Identification and risk assessment of soldering failure sources using a hybrid failure mode and effect analysis model and a fuzzy inference system

Abstract

This study presents a case study using a hybrid failure mode and effect analysis (FMEA) and a fuzzy inference system (FIS) extract critical soldering failure sources and assess their risks in surface mount assembly (SMA). The desired level of soldering quality in SMA plays an important role of achieving a defect-free printed circuit board assembly to fabricate many types of modern electronic products. FMEA is an effective method for identifying potential failures in the product and process in the design stage. However, the traditional FMEA has several disadvantages. To improve soldering quality and overcome the drawbacks in traditional FMEA, the entropy measurement method is integrated with grey relational analysis (GRA) to investigate the correlations between the three FMEA decision factors, chance of failure occurrence, degree of severity, and detection probability, and to determine their importance weights. Finally, an assessment tool for quickly predicting risks of soldering failure sources corresponding to quantitative or qualitative values of the three FMEA decision factors through a developed FIS. The proposed hybrid measurement framework also can be applied for solving other risk evaluation problems.