Accelerated life testing and over-stress testing of transistors

1963 ◽  
Vol 2 (3) ◽  
pp. 191-204 ◽  
Author(s):  
J.M. Groocock
Keyword(s):  
Stress Testing ◽  
Accelerated Life Testing ◽  
Life Testing ◽  
Accelerated Life

Double-Crossed Step-Stress Accelerated Life Testing for Pneumatic Cylinder

2011 ◽  
Vol 121-126 ◽  
pp. 1274-1278 ◽  
Author(s):  
Juan Chen ◽  
De Yi Wang ◽  
Yong Ling Fu ◽  
Xiao Ye Qi
Keyword(s):  
Stress Testing ◽  
Estimation Error ◽  
Accelerated Life Testing ◽  
Constant Stress ◽  
Pneumatic Cylinder ◽  
Average Lifetime ◽  
Life Testing ◽  
Failure Data ◽  
Accelerated Life ◽  
Step Down

This paper discusses the principle and method of Double-Crossed Step-Down-Stress Accelerated Life Testing (DCSDS-ALT) for pneumatic cylinders. As to pneumatic cylinder, the step-down-stress testing failure physics can be described as cumulative degradation model. Temperature and frequency are normally chosen as the test stresses. The failure data obtained under DCSDS-ALT testing steps can be converted to those under constant stress testing. And the reliability specifications can be derived accordingly. To compare Double-stress ALTs with traditional constant stress testing shows Double-stress ALTs can meet the accuracy demand. The 5% of average lifetime estimation error and 1.85% of the characteristic lifetime error are very satisfying for pneumatic industrial lifetime prediction.

Double Crossed Step-Down-Stress Accelerated Life Testing for Pneumatic Cylinder Based on Cumulative Damage Model

2013 ◽  
Vol 871 ◽  
pp. 56-63 ◽  
Author(s):  
Juan Chen ◽  
Jia Li ◽  
De Yi Wang ◽  
Dian Liang Fan ◽  
Xiao Ye Qi
Keyword(s):  
Stress Testing ◽  
Stress Test ◽  
Cumulative Damage ◽  
Accelerated Life Testing ◽  
Constant Stress ◽  
Pneumatic Cylinder ◽  
Life Testing ◽  
Failure Data ◽  
Accelerated Life ◽  
Step Down

Double Crossed Step-Down-Stress Accelerated Life Testing (DCSDS-ALT) discussed in this paper was implemented by switch down the double stresses alternately. Compared to constant stress test, step-stress test decreased specimen numbers, time and cost, and eventually well improve the accelerated testing efficiency. For pneumatic cylinder, the step-down-stress testing failure physics can be described as cumulative degradation model. By use of cumulative damage General Log-Linear relationship and Weibull assumption, the failure data obtained were equivalently converted to failure data under constant stress testing. Then the reliability specifications can be derived with better accuracy. The 5% of average lifetime estimation error and 1.85% of the characteristic lifetime error are very satisfying for pneumatic industrial lifetime prediction.

ACCELERATED LIFE TESTING OF COMPONENTS OF NUCLEAR RESEARCH REACTORS

2016 ◽  
Author(s):  
Vanderley Vasconcelos ◽  
WELLINGTON SOARES ◽  
Antonio Carlos Lopes da Costa ◽  
Raíssa Oliveira Marques
Keyword(s):  
Nuclear Research ◽  
Accelerated Life Testing ◽  
Life Testing ◽  
Research Reactors ◽  
Accelerated Life

scholarly journals Bayesian estimation of the parameters of the bivariate generalized exponential distribution using accelerated life testing under censoring data

2015 ◽  
Vol 3 (2) ◽  
pp. 215
Author(s):  
Abd El-Maseh, M. P
Keyword(s):  
Bayesian Estimation ◽  
Accelerated Life Testing ◽  
Constant Stress ◽  
Type I ◽  
Life Testing ◽  
Unknown Parameters ◽  
Numerical Studies ◽  
Inverse Power Law ◽  
Accelerated Life ◽  
Power Law Function

<p>In this paper, the Bayesian estimation for the unknown parameters for the bivariate generalized exponential (BVGE) distribution under Bivariate censoring type-I samples with constant stress accelerated life testing (CSALT) are discussed. The scale parameter of the lifetime distribution at constant stress levels is assumed to be an inverse power law function of the stress level. The parameters are estimated by Bayesian approach using Markov Chain Monte Carlo (MCMC) method based on Gibbs sampling. Then, the numerical studies are introduced to illustrate the approach study using samples which have been generated from the BVGE distribution.</p>

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