Research on Lifespan Prediction Methods Using Ultrasonic Microimaging for Electronic Packaging
Source abstract
Abstract
Addressing the issue of lifespan prediction for electronic packages under thermal loading, this paper proposes a method for predicting the lifespan of electronic packages based on ultrasonic microimaging. Firstly, experimental samples equipped with flip-chip packages were designed and fabricated and subjected to aging through thermal cycle acceleration tests. Ultrasonic microscopy was utilized to periodically acquire ultrasonic image data for monitoring solder joint degradation. Secondly, the internal ultrasonic wave propagation mechanism within electronic packages was investigated, establishing a qualitative relationship between the intensity in the central region of the solder joint’s ultrasonic image and internal defects within the joint. Image processing techniques were applied to enhance the quality of the solder joint images, and the mean intensity in the central region of the solder joint image was extracted as a failure feature. Finally, based on the extracted failure feature, a data-driven failure model for solder joints was developed, which predicts the lifespan of the solder joints based on cumulative failure probability. The research results indicate that the proposed model accurately describes the failure process of solder joints and effectively differentiates the lifespan variations among solder joints at different locations on the chip. This provides theoretical support for the reliability assessment of electronic package solder joints and holds practical value for enhancing the overall reliability of electronic packaging components.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electronic Packaging and Soldering Technologies · Integrated Circuits and Semiconductor Failure Analysis · Industrial Vision Systems and Defect Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Xi’an University of Science and Technology, Xi’an 710054, China
School of Mechanical Engineering, Liverpool John Moores University, Liverpool L3 3AF, UK
Funding
National Natural Science Foundation of China · Newton Fund · National Key R&D Program of China · EU H2020-Marie Sklodowska-Curie research and innovation staff exchange 2019 grant
References (24)
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