Planning of Accelerated Life Tests With Dependent Failure Modes Based on a Gamma Frailty Model

Technometrics ◽  
2012 ◽  
Vol 54 (4) ◽  
pp. 398-409 ◽  
Author(s):  
Xiao Liu
Keyword(s):  
Failure Modes ◽  
Frailty Model ◽  
Accelerated Life Tests ◽  
Gamma Frailty ◽  
Accelerated Life ◽  
Life Tests ◽  
Dependent Failure

Hygro-Mechanical Durability of Underfilled Flip-Chip-on-Board (FCOB) Interconnects

2002 ◽  
Vol 124 (3) ◽  
pp. 184-187 ◽  
Author(s):  
J. H. Okura ◽  
A. Dasgupta ◽  
J. F. J. M. Caers
Keyword(s):  
Flip Chip ◽  
Failure Modes ◽  
Moisture Absorption ◽  
Accelerated Aging ◽  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Service Durability ◽  
Mechanical Durability ◽  
Life Tests ◽  
And Diffusion

The effect of constant temperature and humidity environments on the durability of interconnects in underfilled Flip-Chip-on-Board (FCOB) assemblies is investigated in this study. Polymeric underfills, used to enhance thermomechanical durability of the interconnects, are found to create new failure modes due to hygromechanical swelling. Based on experimental observations, the failure mechanism is hypothesized to be cracking of intermetallics, which have weakened due to thermal aging. Pseudo 3-D finite element analyses are conducted to quantify the moisture absorption and diffusion through the polymeric underfill, and the resulting hygromechanical viscoplastic stress history. The simulations are combined with accelerated aging tests to assess in-service durability in hot, humid environments. Model predictions are compared with results of accelerated life tests available in the literature.

Effect of Moisture on Durability of Flip-Chip-on-Board (FCOB) Interconnects

2000 ◽  
Author(s):  
J. H. Okura ◽  
A. Dasgupta ◽  
J. F. J. M. Caers
Keyword(s):  
Flip Chip ◽  
Failure Modes ◽  
Moisture Absorption ◽  
Accelerated Aging ◽  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Model Predictions ◽  
Service Durability ◽  
Life Tests ◽  
And Diffusion

Abstract The effect of constant temperature and humidity environments on the durability of interconnects in underfilled Flip-Chip-on-Board (FCOB) assemblies is investigated in this study. Polymeric underfills, used to enhance thermomechanical durability of the interconnects, are found to create new failure modes due to hygromechanical swelling. Based on experimental observations, the failure mechanism is hypothesized to be cracking of intermetallics, which have weakened due to thermal aging. Pseudo 3-D finite element analyses are conducted to quantify the moisture absorption and diffusion through the polymeric underfill, and the resulting hygromechanical viscoplastic stress history. The simulations are combined with accelerated aging tests to assess in-service durability in hot, humid environments. Model predictions are compared with results of accelerated life tests available in the literature.

ANALYSES OF ACCELERATED LIFE TEST DATA UNDER TWO FAILURE MODES

2002 ◽  
Vol 09 (02) ◽  
pp. 111-125 ◽  
Author(s):  
C. M. KIM ◽  
D. S. BAI
Keyword(s):  
Failure Mode ◽  
Data Model ◽  
Failure Modes ◽  
Location Parameter ◽  
Estimation Procedure ◽  
Accelerated Life Test ◽  
Simulation Studies ◽  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Life Tests

This paper proposes a method of estimating the lifetime distribution at use condition for constant stress accelerated life tests when an extrinsic failure mode as well as intrinsic one exists. A mixture of two distributions is introduced to describe these failure modes. It is assumed that the log lifetime of each failure mode follows a location-scale distribution and a linear relation exists between the location parameter and the stress. An estimation procedure using the expectation and maximization algorithm is proposed and specific formulas for Weibull distribution are obtained. Simulation studies are performed to investigate the properties of the estimates and the effects of stress level. Numerical comparisons with the masked data model are also performed.

Accelerated Life Tests with Competing Failure Modes

2019 ◽  
pp. 197-221
Author(s):  
Kanchan Jain ◽  
Preeti Wanti Srivastava
Keyword(s):  
Failure Modes ◽  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Life Tests

scholarly journals Leveraging Label Information in a Knowledge-Driven Approach for Rolling-Element Bearings Remaining Useful Life Prediction

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2163
Author(s):  
Tarek Berghout ◽  
Mohamed Benbouzid ◽  
Leïla-Hayet Mouss
Keyword(s):  
Transfer Learning ◽  
Short Term Memory ◽  
Remaining Useful Life ◽  
Accelerated Life Tests ◽  
Learning Path ◽  
Accelerated Life ◽  
Unseen Data ◽  
Label Information ◽  
Life Tests ◽  
Ill Posed

Since bearing deterioration patterns are difficult to collect from real, long lifetime scenarios, data-driven research has been directed towards recovering them by imposing accelerated life tests. Consequently, insufficiently recovered features due to rapid damage propagation seem more likely to lead to poorly generalized learning machines. Knowledge-driven learning comes as a solution by providing prior assumptions from transfer learning. Likewise, the absence of true labels was able to create inconsistency related problems between samples, and teacher-given label behaviors led to more ill-posed predictors. Therefore, in an attempt to overcome the incomplete, unlabeled data drawbacks, a new autoencoder has been designed as an additional source that could correlate inputs and labels by exploiting label information in a completely unsupervised learning scheme. Additionally, its stacked denoising version seems to more robustly be able to recover them for new unseen data. Due to the non-stationary and sequentially driven nature of samples, recovered representations have been fed into a transfer learning, convolutional, long–short-term memory neural network for further meaningful learning representations. The assessment procedures were benchmarked against recent methods under different training datasets. The obtained results led to more efficiency confirming the strength of the new learning path.

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