Health monitoring technologies, which can evaluate the performance degradation, load history and degree of fatigue, have the potential to improve the maintenance, the reliability design method and the availability in improper use conditions of electronic equipment. In this paper, we propose a method to assess the cooling performance degradation and load history of printed circuit boards in electronic equipment by use of a hierarchical Bayes model based on CAE (Computer Aided Engineering) results of thermal stress simulation and experiment data from actual measurements. We applied this method to a notebook PC that can monitor the device load factor and revolution number of cooling fan. It is shown that this method can estimate the temperature and deformation distribution of the printed circuit board from monitoring variables through latent variables such as thermal dissipation of the device and thermal boundary condition by use of the hierarchical Bayes model. And it is confirmed that the statistical load assessment concerning thermal cyclic load and the maximum load distribution can be conducted using the estimated temperature and deformation data. We verified that the cooling performance degradation can be assessed, if the temperature difference per unit thermal value between two suitable points on the printed circuit board can be obtained. Furthermore, we attempted the estimation method based on the hierarchical Bayes model to dynamic load assessment such as cyclic drop impact for PCB. The assessment method for the strain range distribution of the solder joints on the PCB was conducted to lead to the conservative results for reliability design. It is concluded that the proposed method can be effective to assess the field load history and cooling performance degradation.

A quench is the transition from a superconducting state to a normal conducting state. Elucidating the mechanism of quenching caused by mechanical disturbances (training quench) requires a detailed understanding of the stress state in the coil during excitation. In this study, we developed a large-scale analysis method that can precisely analyze where strain energy is concentrated and loss energy is generated due to thermal stress and electromagnetic force in superconducting coils by considering the detailed structure of superconducting wires and the wire alignment disorder caused by constraints during winding. The results showed that strain energy in the resin is concentrated in the region of overlap between the strain energy distribution caused by the macroscopic deformation of the coil and the geometrically inhomogeneous region, including the wire transfer zone. Furthermore, comparative verification using acoustic emission measurements to determine damage locations suggests that quench is also concentrated at the transfer zone in the actual coil, thus demonstrating the validity of the analysis. A sub-model of the area around the transfer zone, which was found in the large-scale analysis, was created, and crack propagation analysis was conducted using the phase-field method. Crack propagation in the resin and increased deformation of the wire due to weakening of the supporting rigidity of the wire caused by the crack propagation were observed.

Devices mounted on printed circuit boards (PCBs) are subject to temperature variations resulting from power switching and ambient temperature changes, and may be subject to random dynamic load histories from sources such as vibration. Since solder material is mechanically the most ductile part, fatigue failure may occur in solder joints. Health monitoring for fatigue life under field conditions is a key issue for improving availability and serviceability for maintenance. We have developed a failure precursor detection technology and a fatigue life estimation method for ball grid array (BGA) solder joints, based on a canary circuit. This method estimates fatigue failure life of an actual circuit by detecting failure connections in a canary circuit (a dummy circuit of daisy-chained solder joints). The canary circuit is designed to fail before the actual circuit under the same failure mode by using accelerated reliability testing and inelastic stress simulation. A feasibility study of the failure probability estimation method is conducted by applying the method to a PCB on which a BGA component is mounted. It is confirmed that the fatigue life under a thermal cyclic load can be estimated from a canary circuit, that estimation of fatigue life under a random dynamic load is feasible, and that the estimation results are consistent with results from actual random vibration tests. The proposed method is found to be useful for prognostic health monitoring of solder joint fatigue failure.

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.

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