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Man Ho Ling - One of the best experts on this subject based on the ideXlab platform.

  • Constant Stress accelerated life test models and data analysis for one shot devices
    2016
    Co-Authors: N Balakrishnan, Man Ho Ling
    Abstract:

    In reliability analysis, accelerated life-tests are commonly used for inducing rapid failures, thus producing more lifetime information in a relatively short period of time. A link function relating Stress levels and lifetimes is then utilized to extrapolate lifetimes of units from accelerated conditions to normal operating conditions. In the context of one-shot device testing, encountered commonly in testing devices such as munitions, rockets, and automobile air bags, either left- or right-censored data are collected instead of actual lifetimes of the devices under test. In this chapter, we study binary response data of one-shot devices collected from Constant-Stress accelerated life-tests, and discuss the analysis of such one-shot device testing data under accelerated life-tests based on parametric and semi-parametric models. In addition, a competing risks model is introduced into the one-shot device testing analysis under Constant-Stress accelerated life-test setting. Finally, some numerical examples are presented to illustrate the models and inferential results discussed here.

  • Best Constant-Stress Accelerated Life-Test Plans With Multiple Stress Factors for One-Shot Device Testing Under a Weibull Distribution
    IEEE Transactions on Reliability, 2014
    Co-Authors: Narayanaswamy Balakrishnan, Man Ho Ling
    Abstract:

    We discuss here the design of Constant-Stress accelerated life-tests for one-shot device testing by assuming a Weibull distribution as a lifetime model. Because there are no explicit expressions for the maximum likelihood estimators of the model parameters and their variances, we adopt the asymptotic approach here to develop an algorithm for the determination of optimal allocation of devices, inspection frequency, and the number of inspections at each Stress level, by assuming a Weibull distribution with non-Constant scale and shape parameters as the lifetime distribution. The asymptotic variance of the estimate of reliability of the device at a specified mission time is minimized subject to a pre-fixed experimental budget, and a termination time. Examples are provided to illustrate the proposed algorithm for the determination of the best test plan. A sensitivity analysis of the best test plan is also carried out to examine the effect of misspecification of the model parameters.

Ali A Ismail - One of the best experts on this subject based on the ideXlab platform.

  • optimum Constant Stress partially accelerated life test plans using type i censored data from the inverse weibull distribution
    Strength of Materials, 2017
    Co-Authors: Ali A Ismail, Al A Tamimi
    Abstract:

    In this paper, a Constant Stress partially accelerated life test (CSPALT) model is presented and analyzed using type-I censored data from the inverse Weibull distribution. The maximum likelihood estimates (point and interval) of the distribution parameters and the acceleration factor are obtained. CSPALT plans are developed. The proportion of test units that should be allocated to run under accelerated condition is optimally determined. To demonstrate the theoretical results, simulation studies are made.

  • on designing Constant Stress partially accelerated life tests under time censoring
    Strength of Materials, 2014
    Co-Authors: Ali A Ismail
    Abstract:

    It is not easy to obtain more failure data from products with high quality and long life at normal (use) condition. Thus, accelerated tests are needed in this respect. This paper considers the Constant Stress partially accelerated life tests with type-I censoring under Weibull distribution. The maximum likelihood estimators of the model parameters are derived. Partially accelerated life tests plans are developed such that the generalized asymptotic variance of the maximum likelihood estimators of the model parameters is minimized. The plan is to specify the proportion of test units that should be allocated to run under use condition. Simulation studies are made for illustrative purposes.

  • estimating the generalized exponential distribution parameters and the acceleration factor under Constant Stress partially accelerated life testing with type ii censoring
    Strength of Materials, 2013
    Co-Authors: Ali A Ismail
    Abstract:

    UDC 539.4 Accelerated life testing (ALT) and partially accelerated life testing (PALT) are frequently used in modern reliability engineering. ALT and PALT are run to obtain information on the life of the products and materials in a shorter time and at lower cost. The experimental units are subject to Stress conditions that are more severe than those encountered in normal use condition to induce early failures. ALT or PALT can be carried out using Constant, step, progressive, cyclic and random Stress loadings. This paper considers the problem of estimating the generalized exponential (GE) distribution parameters and the acceleration factor under Constant-Stress PALT model. The main objective is to derive the maximum likelihood estimators (MLEs) of the parameters of the GE distribution and the acceleration factor when the data are type-II censored from Constant-Stress PALT. Also, the performance of the MLEs is investigated numerically for different sample sizes and different parameter values using the mean square error. In addition, the approximate confidence intervals of the model parameters are constructed. Moreover, the likelihood ratio bounds (LRB) method is used to obtain confidence bounds of the model parameters when the sample size is small. For illustration, a simulation study is conducted. It is observed that the simulation results support the theoretical findings.

  • optimum Constant Stress life test plans for pareto distribution under type i censoring
    Journal of Statistical Computation and Simulation, 2011
    Co-Authors: Ali A Ismail, Abdalla Abdelghaly, Eman H Elkhodary
    Abstract:

    The paper considers the case of Constant-Stress partially accelerated life testing (CSPALT) when two Stress levels are involved under type-I censoring. The lifetimes of test items are assumed to follow a two-parameter Pareto lifetime distribution. Maximum-likelihood method is used to estimate the parameters of CSPALT model. Confidence intervals for the model parameters are constructed. Optimum CSPALT plans that determine the best choice of the proportion of test units allocated to each Stress are developed. Such optimum test plans minimize the generalized asymptotic variance of the maximum-likelihood estimators of the model parameters. For illustration, Monte Carlo simulation studies are presented.

Xuchao Bai - One of the best experts on this subject based on the ideXlab platform.

  • statistical analysis of dependent competing risks model in Constant Stress accelerated life testing with progressive censoring based on copula function
    Statistical Theory and Related Fields, 2018
    Co-Authors: Xuchao Bai, Yimin Shi, Yiming Liu, Bin Liu
    Abstract:

    In this paper, we consider the statistical analysis for the dependent competing risks model in the Constant Stress accelerated life testing with Type-II progressive censoring. It is focused on two competing risks from Lomax distribution. The maximum likelihood estimators of the unknown parameters, the acceleration coefficients and the reliability of unit are obtained by using the Bivariate Pareto Copula function and the measure of dependence known as Kendall's tau. In addition, the 95% confidence intervals as well as the coverage percentages are obtained by using Bootstrap-p and Bootstrap-t method. Then, a simulation study is carried out by the Monte Carlo method for different measures of Kendall's tau and different testing schemes. Finally, a real competing risks data is analysed for illustrative purposes. The results indicate that using copula function to deal with the dependent competing risks problems is effective and feasible.

  • inference for Constant Stress accelerated life tests with dependent competing risks from bivariate birnbaum saunders distribution based on adaptive progressively hybrid censoring
    IEEE Transactions on Reliability, 2017
    Co-Authors: Chunfang Zhang, Yimin Shi, Xuchao Bai
    Abstract:

    In life testing, the competing risks model is usually discussed under the assumption of independence. In this paper, we consider a dependent competing risks model using bivariate Birnbaum–Saunders distribution in Constant-Stress accelerated life testing. To observe expected failure times and terminate the life tests around a predetermined time, the adaptive progressively hybrid censoring scheme is adopted. Based on the accelerated competing risks model with the adaptive progressively hybrid censoring scheme, we obtain the maximum-likelihood estimators, approximate confidence intervals, and bootstrap confidence intervals of unknown parameters. To test the independence between the bivariate competing risks and find the relationship of shape and scale parameters, we discuss the likelihood ratio tests for hypotheses of interest. In addition, we compute the maximum-likelihood predictors of unobserved competing risks times in the Constant-Stress accelerated life tests. Finally, a simulation study and an illustrative example are provided to support the proposed model and methods, and to examine the performance of estimators and testing.

Xiangzhong Fang - One of the best experts on this subject based on the ideXlab platform.

  • exact confidence limits for the acceleration factor under Constant Stress partially accelerated life tests with type i censoring
    IEEE Transactions on Reliability, 2018
    Co-Authors: Deqiang Zheng, Xiangzhong Fang
    Abstract:

    In modern lifetime assessment and reliability analysis, accelerated life test has frequently been used to yield information quickly so that the life distribution of products can be estimated. This paper considers the estimate of the acceleration factor for the exponentially distributed lifetimes under the Constant-Stress partially accelerated life test with Type-I censored data. In many applications with small sample sizes, the approximate confidence limits for the parameters based on large-sample asymptotic distributions or the bootstrap method are usually not accurate enough. This study defines two ordering relations on the sample space by the generalized maximum likelihood estimator of the acceleration factor, and proposes one new approach of constructing the exact lower and upper confidence limits for the acceleration factor. An efficient procedure of computing the exact lower and upper confidence limits for the acceleration factor is presented via the EM algorithm. The approximate confidence limits for the acceleration factor using the asymptotic and bootstrap methods are also derived in this study. The proposed exact approach is compared with the two approximate methods by carrying out extensive simulation studies, and it is shown that the exact method performs well and is robust in small sample settings. Finally, we present a real example of the accelerated life test to illustrate all methods studied in this paper.

Syuanrong Huang - One of the best experts on this subject based on the ideXlab platform.