Search

Bias temperature instability represents a significant reliability concern for mosfets, leading to the degeneration of critical operational parameters. Effective identification of path dependence is a prerequisite to ensure that cumulative degradation under the mission profile can be accurately quantified, which involves determining whether the stress interactions affect the degradation. Despite its importance, path dependence is often overlooked, potentially compromising the reliability prediction. This article presents a method for identifying the path dependence that may be inherent to the degradation process, including accelerated degradation test design and path dependence analysis. The practicality and effectiveness of the proposed method are demonstrated through experiments on silicon mosfets, revealing its ability to identify path dependence and provide quantitative evaluation. Empirical results indicate that identical degradation parameters may not necessarily equate to a uniform physical condition of the material. Therefore, it is imperative to exercise increased caution when utilizing traditional models for cumulative degradation computations.

The traditional method assesses the impact of fractures on electronics by calculating test results for many samples, which ignores variation in manufacturing parameters between individuals and does not accurately reflect the actual state. This article proposes a fracture analysis method for multilayer ceramic capacitors (MLCC) by the phase field because of complex structures and diverse manufacturing parameters. This method is based on Griffith’s theory, and the phase field to calculate crack expansion and fracture effects on the electric potential of MLCC is obtained. Finally, MLCC of packages 0603, 1210, and 2220 are studied as numerical examples of applications for investigation. Calculated results are consistent with tests, which verifies the accuracy of this method. In addition, the mechanism of the MLCC fracture on its electrical characteristics is given, and the impact of solder height and the internal electrode number on the fracture are analyzed using this method.

Accidents of launch vehicles, satellites, and missiles originating from remainder particles account for 6% of the causes in accident investigations. The problem of remainder particles seriously reduces the reliability of sealed electronic components in aerospace. Numerous cases have shown that remainder particles cannot be completely avoided due to process, environment, and other factors. As an important method for detecting remainder particles, the particle impact noise detection (PIND) method has become a standard testing tool in the aerospace field in China. However, there is still a lack of effective and feasible solutions to the problems of sensor sensitivity measurement and consistency evaluation, which are key and indispensable components of the closed-loop process of the PIND method. Through numerous experiments, this article proposed a complete set of new methods and systems for the sensitivity measurement of PIND sensors, allowing real-time measurement of PIND sensor sensitivity at the production site without moving or disassembling the sensor. This article systematically illustrated the feasibility of this new method and system from the perspective of measurement method, measurement system, measurement result verification, and measurement system application. The accuracy and feasibility of the proposed method were verified using the free-field underwater comparison method. The average difference between the two methods was less than 1 dB (1 V/ $\mu $ bar), which meets the practical requirements (±3 dB). In addition, the coupling effect of different coupling agents, the full contact time of coupling agents, and the epoxy adhesive bonding process were further analyzed based on the proposed method and system, and satisfactory improvement results were obtained.

The design optimization of a robust, low-cost, and high-quality permanent magnet actuator (PMA) that meets the requirements of industrial applications presents numerous challenges. In particular, uncertainties arising from fabrication, assembly, and degradation are omnipresent and can produce erratic or infeasible solutions, complicating the robust design optimization (RDO) for PMAs. State-of-art RDO approaches treat these uncertainties as fixed contribution margins while disregarding the changes in the contribution margin, manufacturing cost, and life-cycle quality loss resulting from variations in uncertainty range and time-variant degradation. To address these issues, we propose a heuristic RDO approach for the batch production of PMAs that considers the manufacturing cost, life-cycle quality loss, and adaptive iterative step size to address these issues. Firstly, a unified manufacturing cost model is innovated to assess the complex component morphologies. Subsequently, a life-cycle dynamic quality loss model considering the time-variant degradation is established by applying the modified quality loss function, which can effectively track the losses caused by fluctuations in life-cycle quality. Based on the manufacturing cost and life-cycle quality loss models, a heuristic RDO approach with an adaptive iterative step size model is proposed, which automatically assigns the maximum bound of uncertainties and reduces the quality variation without significantly increasing manufacturing cost. Finally, a case study on a latching rotary PMA is used to illustrate the effectiveness of the proposed approach through simulation and experiment. This method achieves a 35.8% increase in robustness for batch-produced PMAs along with a 100% reduction in life-cycle quality losses at only a marginal increase of 5.9% in manufacturing costs.