An Approach to Assess Solder Interconnect Degradation Using Digital Signal

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An Approach to Assess Solder Interconnect Degradation Using Digital Signal
Yoon, Jeong-ah
Kwon, Daeil
Issue Date
Graduate School of UNIST
Digital signals used in electronic systems require reliable data communication. It is necessary to monitor the system health continuously to prevent system failure in advance. Solder joints in electronic assemblies are one of the major failure sites under thermal, mechanical and chemical stress conditions during their operation. Solder joint degradation usually starts from the surface where high speed signals are concentrated due to the phenomenon referred to as the skin effect. Due to the skin effect, high speed signals are sensitive when detecting the early stages of solder joint degradation. The objective of the thesis is to assess solder joint degradation in a non-destructive way based on digital signal characterization. For accelerated life testing the stress conditions were designed in order to generate gradual degradation of solder joints. The signal generated by a digital signal transceiver was travelling through the solder joints to continuously monitor the signal integrity under the stress conditions. The signal properities were obtained by eye parameters and jitter, which represented the characteristics of the digital signal in terms of noise and timing error. The eye parameters and jitter exhibited significant increase after the exposure of the solder joints to the stress conditions. The test results indicated the deterioration of the signal integrity resulted from the solder joint degradation, and proved that high speed digital signals could serve as a non-destructive tool for sensing physical degradation. Since this approach is based on the digital signals used in electronic systems, it can be implemented without requiring additional sensing devices. Furthermore, this approach can serve as a proactive prognostic tool, which provides real-time health monitoring of electronic systems and triggers early warning for impending failure.
Department of Human and Systems Engineering
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