scholarly journals Statistical Inference Under Step Stress Partially Accelerated Life Testing for Adaptive Type-II Progressive Hybrid Censored Data

2021 ◽  
Author(s):  
Mustafa Kamal ◽  
Ahmadur Rahman ◽  
Shazia Zarrin ◽  
Haneefa Kausar
Keyword(s):  
Information Matrix ◽  
Real Life ◽  
Optimality Criteria ◽  
Accelerated Life Testing ◽  
Model Parameters ◽  
Type Ii ◽  
Life Testing ◽  
Suggested Approach ◽  
Accelerated Life ◽  
The Impact

Accelerated life tests (ALTs) are designed to investigate the lifetime of extraordinarily reliable things by exposing them to increased stress levels of stressors such as temperature, voltage, pressure, and so on, in order to cause early breakdowns. The Nadarajah-Haghighi (NH) distribution is of tremendous importance and practical relevance in many real-life scenarios due to its attractive qualities such as its density function always has a zero mode and its hazard rate function can be increasing, decreasing, or constant. In this article, the NH distribution is considered as a lifetime distribution under the step stress partially accelerated life testing (SSPALT) model with adaptive type II progressively hybrid censored samples. The unknown model parameters and acceleration factors are estimated using maximum likelihood estimation (MLE) method assuming that the impact of stress change in SSPALT is explained by a tampered random variable (TRV) model. The Fisher information matrix, which is based on large sample theory, is also constructed and used to produce the approximate confidence intervals (ACIs). Furthermore, two potential optimum test strategies based on the A and D optimality criteria are evaluated. To investigate the performance of the proposed methodologies and statistical assumptions established in this article, extensive simulations using R software have been conducted. Finally, to further illustrate the suggested approach, a real-world example based on the times between breakdowns for a repairable system has been provided.

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.

Condition monitoring of aluminium electrolytic capacitors using accelerated life testing

2018 ◽  
Vol 35 (8) ◽  
pp. 1671-1682 ◽  
Author(s):  
Cherry Bhargava ◽  
Vijay Kumar Banga ◽  
Yaduvir Singh
Keyword(s):  
Failure Time ◽  
Accelerated Life Testing ◽  
New Method ◽  
Equivalent Series Resistance ◽  
Life Testing ◽  
Content Type ◽  
Electrolytic Capacitors ◽  
Accelerated Life ◽  
Accuracy Level ◽  
The Impact

Purpose An electrolytic capacitor is extensively used as filtering devices in various power supplies and audio amplifiers. Low cost and higher value of capacitance make it more well known. As environmental stress and electrical parameters increase, capacitors degrade on accelerated pace. The paper aims to discuss these issues. Design/methodology/approach This paper focusses on the impact of thermal stress on electrolytic capacitors using accelerated life testing technique. The failure time was calculated based on the change in capacitance, equivalent series resistance and weight loss. The experimental results are compared with the outcome of already available life monitoring methods, and the accuracy level of these methods is accessed. Findings The results of all the three methods are having maximum 55 per cent accuracy. To enhance the accuracy level of theoretical methods, modifications have been suggested. A new method has been proposed, whose outcome is 92 per cent accurate with respect to experimentally obtained outcomes. Practical implications To assess the capacitor’s reliability using an experimental and modified theoretical method, failure prediction can be done before it actually fails. Originality/value A new method has been proposed to access the lifetime of capacitor.

scholarly journals MCMC Method for Exponentiated Lomax Distribution based on Accelerated Life Testing with Type I Censoring

2021 ◽  
Vol 20 ◽  
pp. 319-334
Author(s):  
Refah Alotaibi ◽  
H. Rezk ◽  
Sanku Dey
Keyword(s):  
Accelerated Life Testing ◽  
Constant Stress ◽  
Estimation Methods ◽  
Model Parameters ◽  
Type I ◽  
Life Testing ◽  
Informative Priors ◽  
Lomax Distribution ◽  
Type I Censoring ◽  
Accelerated Life

Accelerated Life Testing (ALT) is an effective technique which has been used in different fields to obtain more failures in a shorter period of time. It is more economical than traditional reliability testing. In this article, we propose Bayesian inference approach for planning optimal constant stress ALT with Type I censoring. The lifetime of a test unit follows an exponentiated Lomax distribution. Bayes point estimates of the model parameters and credible intervals under uniform and log-normal priors are obtained. Besides, optimum test plan based on constant stress ALT under Type I censoring is developed by minimizing the pre-posterior variance of a specified low percentile of the lifetime distribution at use condition. Gibbs sampling method is used to find the optimal stress with changing time. The performance of the estimation methods is demonstrated for both simulated and real data sets. Results indicate that both the priors and the sample size affect the optimal Bayesian plans. Further, informative priors provide better results than non-informative priors.

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