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Predicting the Lifetime of the PCB

Predicting the Lifetime of the PCB
This paper examines a concept to enable the prediction of the lifetime of the PCB using accelerated testing methods and finite element simulations.
Analysis Lab


Authored By:

Markus Leitget, AT&S
Peter Fuchs, PCCL
Leoben, Austria



Two major drivers in the electronic industry are electrical and mechanical miniaturization. Both induce major changes in the material selection as well as in the design.

Nevertheless, the mechanical and thermal reliability of a PCB has to remain at the same high level.

To achieve these reliability targets, extensive testing has to be done with bare PCB as well as assembled PCB.

These tests are time consuming and cost intensive.

The PCBs have to be produced, assembled, tested and finally a detailed failure analysis is required to be performed.

This paper examines the development of our concept and has the potential to enable the prediction of the lifetime of the PCB using accelerated testing methods and finite element simulations.

The method of evaluation for the developed concept uses the mechanical loading (drop test) on Printed Circuit Board Assembly test vehicles.

The aim of this study is to show, that experiments on material specimens in combination with corresponding simulation models, allow a significant reduction of previously required board level tests.


The initial task at hand was to evaluate a concept to predict the timeline of PCBs by creating a simulation model.

The authors found a correlation between the Board Level Drop Test and the Board Level Cycling Bend Test.

Therefore, the Board Level Drop Test can be replaced and the Board Level Cycling Bend Test can be used as a Quick Test to check new materials.

The in-plane material data of the individual glass reinforced layers was experimentally determined, while the out-of-plane data was determined using a micromechanics approach.

The combination of Board Level Cycling Bend Test at different amplitudes and the local loading simulations will allow the generation of characteristic failure curves.

Based on these characteristic failure curves, a possible lifetime prediction methodology was suggested.

Initially Published in the IPC Proceedings


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