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Research Papers

Prognostic Health Monitoring Method for Fatigue Failure of Solder Joints on Printed Circuit Boards Based on a Canary Circuit

[+] Author and Article Information
Kenji Hirohata

Toshiba Corporation,
Corporate Research & Development Center,
1, Komukai-Toshiba-cho, Saiwai-ku,
Kanagawa, 212-8582, Japan
e-mail: kenji.hirohata@toshiba.co.jp

Yousuke Hisakuni

Toshiba Corporation,
Corporate Research & Development Center,
1, Komukai-Toshiba-cho, Saiwai-ku,
Kanagawa, 212-8582, Japan
e-mail: yousuke.hisakuni@toshiba.co.jp

Takahiro Omori

Toshiba Corporation,
Corporate Research & Development Center,
1, Komukai-Toshiba-cho, Saiwai-ku,
Kanagawa, 212-8582, Japan
e-mail: takahiro1.omori@toshiba.co.jp

1Corresponding author.

Manuscript received November 4, 2017; final manuscript received March 20, 2018; published online May 3, 2018. Assoc. Editor: Shiv Joshi.

ASME J Nondestructive Evaluation 1(3), 031004 (May 03, 2018) (12 pages) Paper No: NDE-17-1105; doi: 10.1115/1.4039938 History: Received November 04, 2017; Revised March 20, 2018

Devices mounted on printed circuit boards (PCBs) are subject to temperature variations resulting from power switching and ambient temperature changes, and may be subject to random dynamic load histories from sources such as vibration. Since solder material is mechanically the most ductile part, fatigue failure may occur in solder joints. Health monitoring for fatigue life under field conditions is a key issue for improving availability and serviceability for maintenance. We have developed a failure precursor detection technology and a fatigue life estimation method for ball grid array (BGA) solder joints, based on a canary circuit. This method estimates fatigue failure life of an actual circuit by detecting failure connections in a canary circuit (a dummy circuit of daisy-chained solder joints). The canary circuit is designed to fail before the actual circuit under the same failure mode by using accelerated reliability testing and inelastic stress simulation. A feasibility study of the failure probability estimation method is conducted by applying the method to a PCB on which a BGA component is mounted. It is confirmed that the fatigue life under a thermal cyclic load can be estimated from a canary circuit, that estimation of fatigue life under a random dynamic load is feasible, and that the estimation results are consistent with results from actual random vibration tests. The proposed method is found to be useful for prognostic health monitoring of solder joint fatigue failure.

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References

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Figures

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Fig. 5

Canary circuit on a PCB

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Fig. 4

Configuration example of health monitoring system based on a daisy-chained canary circuit

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Fig. 3

Flowchart of the health monitoring method for fatigue failure of solder joints based on a daisy-chained canary circuit

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Fig. 2

Fatigue life estimation method based on a canary circuits

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Fig. 1

Health monitoring of electronic products

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Fig. 6

Fatigue life estimation model of solder joints

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Fig. 7

Flowchart of random dynamic load assessment method

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Fig. 10

Thermal cycle tests under three load levels of temperature range, 100, 165, 190 °C

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Fig. 11

Constant amplitude vibration tests under three load levels of acceleration, 20, 30, 40 G

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Fig. 12

Cross section of solder joints exhibiting fatigue cracks after thermal cycle tests and vibration tests

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Fig. 9

Daisy-chained pattern of BGA component and PCB for failure detection of BGA solder joints

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Fig. 8

Method for updating the fatigue life estimation model

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Fig. 17

Experimental acceleration wave forms

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Fig. 18

Experimental history of strain in the PCB

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Fig. 13

Weibull probability plots for TCT results

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Fig. 14

Thermal fatigue life estimation method

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Fig. 15

Thermal cycle tests results in the case of ⊿T = 125 °C

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Fig. 16

Failure time of solder joints subject to random cyclic load

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Fig. 19

Finite element method analysis model of semiconductor module (rigid surfaces were attached on the FEM model of PCB contacted by four boss screws and fixed to the support base through rigid boss screws for PCB support)

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Fig. 20

Eigen-mode of PCB with semiconductor module

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Fig. 21

Sample waveform generation examples based on acceleration spectrum of support points from HALT experiments

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Fig. 22

Stationary spectrum of acceleration history of support points

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Fig. 23

Highly accelerated life test system for random dynamic load testing

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Fig. 24

Stationary spectrum of the strain history in a longitudinal direction of PCB obtained from both actual HALT experiment data and modal analysis data based on FEM

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Fig. 28

Application to health monitoring: estimation of the probability for fatigue failure of actual circuit's solder joints

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Fig. 25

Calibrated fatigue life estimation model and statistical assessment results for random dynamic load

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Fig. 26

Prior and posterior probability distribution of fatigue life-cycles of canary circuit based on the Bayes method

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Fig. 27

Strain analysis method of solder joints on PCB

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