Prognostic Health Monitoring Method for Fatigue Failure of Solder Joints on Printed Circuit Boards Based on a Canary Circuit

Abstract

Continuing improvements in both capacity and miniaturization of electronic equipment such as solid state drives (SSDs) are spurring demand for high-density packaging of NAND-type flash memory mounted on SSD printed circuit boards. High-density packaging leads to increased fatigue failure risk of solder joints due to the decreased reliability margin for stress. We have developed a failure precursor detection technology based on fatigue failure probability estimation during use. This method estimates the cycles to fatigue failure of an actual circuit by detecting broken connections in a canary circuit (a dummy circuit of daisy-chained solder joints). The canary circuit is designed to fail earlier than the actual circuit under the same failure mode by using accelerated reliability testing and inelastic stress simulation. The statistical distribution of the strain range of solder joints can be provided by Monte Carlo simulations based on the finite element method and random load modeling. A feasibility study of the failure probability estimation method is conducted by applying the method to a printed circuit board on which a ball grid array (BGA) package is mounted using BGA solder joints. The proposed method is found to be useful for prognostic health monitoring of solder joint’s fatigue failure.