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.

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>

scholarly journals Bayesian Estimation and Prediction Based on Constant Stress-Partially Accelerated Life Testing for Topp Leone-Inverted Kumaraswamy Distribution

2021 ◽  
pp. 11-36
Author(s):  
G. R. Al-Dayian ◽  
A. A. El-Helbawy ◽  
R. M. Refaey ◽  
S. M. Behairy
Keyword(s):  
Loss Function ◽  
Accelerated Life Testing ◽  
Constant Stress ◽  
Type Ii ◽  
Life Testing ◽  
Bayes Estimators ◽  
Kumaraswamy Distribution ◽  
Accelerated Life Tests ◽  
Accelerated Life ◽  
Life Tests

Accelerated life testing or partially accelerated life tests is very important in life testing experiments because it saves time and cost. Partially accelerated life tests are used when the data obtained from accelerated life tests cannot be extrapolated to usual conditions. This paper proposes, constant–stress partially accelerated life test using Type II censored samples, assuming that the lifetime of items under usual condition have the Topp Leone-inverted Kumaraswamy distribution. The Bayes estimators for the parameters, acceleration factor, reliability and hazard rate function are obtained. Bayes estimators based on informative priors is derived under the balanced square error loss function as a symmetric loss function and balanced linear exponential loss function as an asymmetric loss function. Also, Bayesian prediction (point and bounds) is considered for a future observation based on Type-II censored under two samples prediction. Numerical studies are given and some interesting comparisons are presented to illustrate the theoretical results. Moreover, the results are applied to real data sets.

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