Reliability Estimation and Failure Analysis of Multilayer Ceramic Chip Capacitors

2003 ◽  
Vol 17 (08n09) ◽  
pp. 1318-1323 ◽  
Author(s):  
Seok Jun Yang ◽  
Jin Woo Kim ◽  
Dong Su Ryu ◽  
Myung Soo Kim ◽  
Joong Soon Jang
Keyword(s):  
Failure Analysis ◽  
Life Stress ◽  
Control Unit ◽  
Accelerated Life Testing ◽  
Reliability Estimation ◽  
Accelerated Life Test ◽  
Root Cause ◽  
Accelerated Life ◽  
Cause Of Failure ◽  
Multilayer Ceramic

This paper presents the failure analysis and the reliability estimation of a multilayer ceramic chip capacitor. For the failed samples used in an automobile engine control unit, failure analysis was made to identify the root cause of failure and it was shown that the migration and the avalanche breakdown were the dominant failure mechanisms. Next, an accelerated life testing was designed to estimate the life of the MLCC. It is assumed that Weibull lifetime distribution and the life-stress relationship proposed Prokopowicz and Vaskas. The life-stress relationship and the acceleration factor are estimated by analyzing the accelerated life test data.

Reliability Evaluation and Failure Analysis for NTC Thermistor

2003 ◽  
Vol 17 (08n09) ◽  
pp. 1254-1260 ◽  
Author(s):  
Joon Sik Jung ◽  
Jin Woo Kim ◽  
Myung Soo Kim ◽  
Joong Soon Jang ◽  
Dong Su Ryu
Keyword(s):  
Life Stress ◽  
Electrical Parameter ◽  
Accelerated Life Test ◽  
Physical Analysis ◽  
Root Cause ◽  
Accelerated Life ◽  
Field Samples ◽  
Ntc Thermistor ◽  
Cause Of Failure ◽  
Non Destructive

Failures of NTC thermistor are analyzed. Visual inspection, electrical parameter test, non-destructive test, and destructive physical analysis were performed on the field samples to identify the root cause of failure. It was found that the predominant failure mechanism was the copper migration of dumet (copper-clad alloy) at glass-PVC interface for glass-coated chip type NTC thermistor molded with PVC. Next, an accelerated life test is designed to predict the lifetime. Temperature, voltage, and humidity are considered as accelerating variables. Under the assumptions of a general life-stress relationship and Weibull lifetime distribution, the parameters of life-stress relationship and acceleration factor for the migration are estimated by analyzing the test data.

scholarly journals Weibull accelerated life testing analysis with several variables using multiple linear regression

DYNA ◽  
2015 ◽  
Vol 82 (191) ◽  
pp. 156-162 ◽  
Author(s):  
Manuel R. Piña-Monarrez ◽  
Carlos A. Ávila-Chávez ◽  
Carlos D. Márquez-Luévano
Keyword(s):  
Life Stress ◽  
Shape Parameter ◽  
Accelerated Life Testing ◽  
Accelerated Life Test ◽  
Likelihood Method ◽  
Test Analysis ◽  
Operational Level ◽  
Accelerated Life ◽  
Response Variance ◽  
Joint Form

In Weibull accelerated life test analysis (ALT) with two or more variables (<em>X<sub>2</sub>, X<sub>3</sub>, ... X<sub>k</sub></em>), we estimated, in joint form, the parameters of the life stress model r{X(t)} and one shape parameter β. These were then used to extrapolate the conclusions to the operational level. However, these conclusions are biased because in the experiment design (DOE) used, each combination of the variables presents its own Weibull family (β<sub>i</sub>, η<sub>i</sub>). Thus the estimated β is not representative. On the other hand, since (β<sub>i</sub>, η<sub>i</sub>) is determined by the variance of the logarithm of the lifetime data σ<sub>t</sub><sup>2</sup> , the response variance σ<sub>y</sub><sup>2</sup> and the correlation coefficient R<sup>2</sup>, which increases when variables are added to the analysis, β is always overestimated. In this paper, the problem is statistically addressed and based on the Weibull families (β<sub>i</sub>, η<sub>i</sub>) a vector Y<sub>η</sub> is estimated and used to determine the parameters of r{X(t)}. Finally, based on the variance σ<sub>y</sub><sup>2</sup> of each level, the variance of the operational level σ<sub>op</sub><sup>2</sup> is estimated and used to determine the operational shape parameter β<sub>op</sub>. The efficiency of the proposed method is shown by numerical applications and by comparing its results with those of the maximum likelihood method (ML).

Case Study—Failure Analysis of a Multiplexer

2016 ◽  
Author(s):  
Michael Woo ◽  
Marcos Campos ◽  
Luigi Aranda
Keyword(s):  
Failure Analysis ◽  
High Reliability ◽  
Component Failure ◽  
Root Cause ◽  
Knowing That ◽  
Cause Of Failure ◽  
The Cost

Abstract A component failure has the potential to significantly impact the cost, manufacturing schedule, and/or the perceived reliability of a system, especially if the root cause of the failure is not known. A failure analysis is often key to mitigating the effects of a componentlevel failure to a customer or a system; minimizing schedule slips, minimizing related accrued costs to the customer, and allowing for the completion of the system with confidence that the reliability of the product had not been compromised. This case study will show how a detailed and systemic failure analysis was able to determine the exact cause of failure of a multiplexer in a high-reliability system, which allowed the manufacturer to confidently proceed with production knowing that the failure was not a systemic issue, but rather that it was a random “one time” event.

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