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Materials 2017, 10(4), 382; doi:10.3390/ma10040382

A Life Prediction Model of Multilayered PTH Based on Fatigue Mechanism

1,2,†,* , 1
Reliability and System Engineering School, Beihang University, Haidian District, Beijing 100191, China
B. John Garrick Institute for the Risk Sciences, University of California, Los Angeles, CA 90095, USA
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editor: Mark T. Whittaker
Received: 15 February 2017 / Revised: 28 March 2017 / Accepted: 29 March 2017 / Published: 4 April 2017
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Plated through hole (PTH) plays a critical role in printed circuit board (PCB) reliability. Thermal fatigue deformation of the PTH material is regarded as the primary factor affecting the lifetime of electrical devices. Numerous research efforts have focused on the failure mechanism model of PTH. However, most of the existing models were based on the one-dimensional structure hypothesis without taking the multilayered structure and external pad into consideration. In this paper, the constitutive relation of multilayered PTH is developed to establish the stress equation, and finite element analysis (FEA) is performed to locate the maximum stress and simulate the influence of the material properties. Finally, thermal cycle tests are conducted to verify the accuracy of the life prediction results. This model could be used in fatigue failure portable diagnosis and for life prediction of multilayered PCB. View Full-Text
Keywords: PTH; multilayer; stress-strain model; fatigue life prediction; FEA; thermal cycling test PTH; multilayer; stress-strain model; fatigue life prediction; FEA; thermal cycling test

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Li, Y.; Hu, W.; Sun, Y.; Wang, Z.; Mosleh, A. A Life Prediction Model of Multilayered PTH Based on Fatigue Mechanism. Materials 2017, 10, 382.

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