An accelerated life test plan for a two-component parallel system under ramp-stress loading using masked data

2018 ◽  
Vol 35 (3) ◽  
pp. 811-820 ◽  
Author(s):  
Preeti Wanti Srivastava ◽  
Savita Savita
Keyword(s):  
Optimality Criterion ◽  
High Reliability ◽  
Parallel System ◽  
Stress Rate ◽  
Accelerated Life Test ◽  
Cumulative Exposure ◽  
Life Test ◽  
Optimal Plan ◽  
Content Type ◽  
Accelerated Life

Purpose Most of the literature on the design of accelerated life test (ALT) plan focus on a single system (subsystem) totally disregarding its internal configuration. Many a times it is not possible to identify the components that cause the system failure or that the cause can only be identified by a subset of its components resulting in a masked observation. The purpose of this paper is to deal with the planning of ramp-stress accelerated life testing for a high-reliability parallel system comprising two dependent components using masked failure data. Such a testing may prove to be useful in a twin-engine aircraft. A ramp-stress results when stress applied on the system increases linearly with time. Design/methodology/approach A parallel system with two dependent components is taken with dependency modeled by Gumbel-Hougaard copula. The stress-life relationship is modeled using inverse power law, and cumulative exposure model is assumed to model the effect of changing stress. The method of maximum likelihood is used for estimating design parameters. The optimal plan consists in finding optimal stress rate using D-optimality criterion. Findings The optimal plan consists in finding optimal stress rate using D-optimality criterion by minimizing the reciprocal of the determinant of Fisher information matrix. The proposed plan has been explained using a numerical example and carrying out a sensitivity analysis. Originality/value The model formulated can help reliability engineers obtain reliability estimates quickly of high-reliability products that are likely to last for several years.

Optimum modified ramp-stress ALT plan with competing causes of failure

2017 ◽  
Vol 34 (5) ◽  
pp. 733-746 ◽  
Author(s):  
Preeti Wanti Srivastava ◽  
Tanu Gupta
Keyword(s):  
Change Point ◽  
Fisher Information Matrix ◽  
High Reliability ◽  
Information Matrix ◽  
Stress Rate ◽  
Accelerated Life Test ◽  
Life Test ◽  
Optimal Plan ◽  
Content Type ◽  
Accelerated Life

Purpose Accelerated life test is undertaken to induce early failure in high-reliability products likely to last for several years. Most of these products are exposed to several fatal risk factors and fail due to one of them. Examples include solar lighting device with two failure modes: capacitor failure, and controller failure. It is necessary to assess each risk factor in the presence of other risk factors as each one cannot be studied in isolation. The purpose of this paper is to explore formulation of optimum time-censored accelerated life test model under modified ramp-stress loading when different failure causes have independent exponential life distributions. Design/methodology/approach The modified ramp-stress uses one test chamber in place of the various chambers used in the normal ramp-stress accelerate life test thus saving experimental cost. The stress-life relationship is modeled by inverse power law, and for each failure cause, a cumulative exposure model is assumed. The method of maximum likelihood is used for estimating design parameters. The optimal plan consists in finding out relevant experimental variables, namely, stress rate and stress rate change point(s). Findings The optimal plan is devised using D-optimality criterion which consists in finding out optimal stress rate and optimal stress rate change point by maximizing logarithm of determinant of Fisher information matrix to the base 10. This criterion is motivated by the fact that the volume of joint confidence region of model parameters is inversely proportional to square root of determinant of Fisher information matrix. The results of sensitivity analysis show that the plan is robust to small deviations from the true values of baseline parameters. Originality/value The model formulated can help reliability engineers obtain reliability estimates quickly of high-reliability products that are likely to last for several years.

Optimum time-censored simple ramp-stress accelerated life test sampling plan for the log-logistic distribution

2015 ◽  
Vol 21 (1) ◽  
pp. 112-132 ◽  
Author(s):  
Preeti Wanti Srivastava ◽  
Deepmala Sharma
Keyword(s):  
Sample Size ◽  
Asymptotic Variance ◽  
Sampling Plan ◽  
Accelerated Life Test ◽  
Test Plan ◽  
Life Test ◽  
Life Distribution ◽  
Optimal Test ◽  
Content Type ◽  
Accelerated Life

Purpose – Acceptance sampling plans are designed to decide about acceptance or rejection of a lot of products on the basis of sample drawn from it. Accelerating the life test helps in obtaining information about the lifetimes of high reliability products quickly. The purpose of this paper is to formulate an optimum time censored acceptance sampling plan based on ramp-stress accelerated life test (ALT) for items having log-logistic life distribution. The log-logistic life distribution has been found appropriate for highly reliable components such as power system components and insulating materials. Design/methodology/approach – The inverse power relationship has been used to model stress-life relationship. It is meant for analyzing data for which the accelerated stress is nonthermal in nature, and frequently used as an accelerating stress for products such as capacitors, transformers, and insulators. The method of maximum likelihood is used for estimating design parameters. The optimal test plan is obtained by minimizing variance of test-statistic that decides on acceptability or rejectibility of lot. The optimal test plan finds optimal sample size, stress rates, sample proportion allocated to each stress and lot acceptability constant such that producer’s risk and consumer’s risk is satisfied. Findings – Asymptotic variance plays a pivotal role in determining the sample size required for a sampling plan for deciding the acceptance/rejection of a lot. The sample size is minimized by optimally designing a ramp-stress ALT so that the asymptotic variance is minimized. Originality/value – The model suggested is of use to quality control and reliability engineers dealing with highly reliable items.

scholarly journals Optimal Plan and Estimation for Bivariate Step-Stress Accelerated Life Test under Progressive Type-I Censoring

2021 ◽  
pp. 683-694
Author(s):  
Mashroor Ahmad Khan ◽  
Navin Chandra
Keyword(s):  
Maximum Likelihood ◽  
Accelerated Life Test ◽  
Maximum Likelihood Estimates ◽  
Cumulative Exposure ◽  
Type I ◽  
Life Test ◽  
Type I Censoring ◽  
Accelerated Life ◽  
Progressive Type ◽  
Stress Levels

 In this paper, a step-stress accelerated life test with two stress variables for Weibull distribution under progressive type-I censoring is considered. The stress-life relationship as a log-linear function of stress levels, and for each combination of stress levels, a cumulative exposure model is assumed. The maximum likelihood and Bayes estimates of the model parameters are obtained. The optimum test plan is developed using variance-optimality criterion, which consists in finding out the optimal stress change time by minimizing asymptotic variance of the maximum likelihood estimates of the log of the scale parameter at the design stress. The proposed study illustrated by using simulated data.

The Statistics Analysis of Degradation Data Based on the Degradation Amount Distribution

2013 ◽  
Vol 791-793 ◽  
pp. 1260-1263
Author(s):  
Yi Zhou He ◽  
Jin Huang Wu ◽  
Yi Dong Wang ◽  
Wei Hua Liu
Keyword(s):  
High Reliability ◽  
Performance Degradation ◽  
Accelerated Life Test ◽  
Test Reliability ◽  
Analysis Method ◽  
Life Test ◽  
Failure Data ◽  
Degradation Data ◽  
Accelerated Life ◽  
Long Life

In order to solve the key technology and method in reliability study of the long-life products, the analysis method of degradation data based on the degradation amount distribution was proposed in this paper. On the basis of statistical model, by analyzing three models of degradation amount distribution, it can be got there is a large number of reliability information with high-reliable and long-life products in performance degradation data. In the case of not getting the failure data by life test and accelerated life test, reliability assessment and life prediction could be carried out for high reliability and long life products with performance degradation data.

The Statistics Analysis of Degradation Data Based on the Degradation Amount Distribution

2013 ◽  
Vol 739 ◽  
pp. 781-784
Author(s):  
Jun Sheng Wang ◽  
Yi Zhou He ◽  
Jin Huang Wu ◽  
Jun Wei Lei
Keyword(s):  
High Reliability ◽  
Performance Degradation ◽  
Accelerated Life Test ◽  
Test Reliability ◽  
Analysis Method ◽  
Life Test ◽  
Failure Data ◽  
Degradation Data ◽  
Accelerated Life ◽  
Long Life

In order to solve the key technology and method in reliability study of the long-life products, the analysis method of degradation data based on the degradation amount distribution was proposed in this paper. On the basis of statistical model, by analyzing three models of degradation amount distribution, it can be got there is a large number of reliability information with high-reliable and long-life products in performance degradation data. In the case of not getting the failure data by life test and accelerated life test, reliability assessment and life prediction could be carried out for high reliability and long life products with performance degradation data.

Approximated optimal design for a bivariate step-stress accelerated life test with generalized exponential distribution under type-I progressive censoring

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nooshin Hakamipour
Keyword(s):  
Accelerated Life Test ◽  
Model Parameters ◽  
Test Design ◽  
Type I ◽  
Test Plan ◽  
Progressive Censoring ◽  
Life Test ◽  
Content Type ◽  
Accelerated Life ◽  
Stress Variable

PurposeIn this paper, the author proposed an optimization design for a step-stress accelerated life test (SSALT) with two stress variables for the generalized exponential (GE) distribution under progressive type-I censoring.Design/methodology/approachIn this paper, two stress variables were considered. Progressive censoring and accelerated life testing were used to reduce the time and cost of testing. It was assumed that the lifetimes of the test units followed a GE distribution. The effects of changing stress were considered as a cumulative exposure model. A log-linear relationship between the scale parameter of the GE distribution and the stress was proposed. The maximum likelihood estimators and approximate and bootstrap confidence intervals (CIs) for the model parameters were obtained. An optimum test plan was developed using minimization of the asymptotic variance (AV) of the percentile life under the usual operating condition.FindingsAccording to the simulation results, the bootstrap CIs of the model parameters gave more accurate results than approximate CIs through the length of CIs. The sensitivity analysis was performed to illustrate the effect of initial estimates on optimal values that has been studied. Simulation results also indicated that the optimal times were not too sensitive to the initial values of parameters; thus, the proposed design was robust.Originality/valueIn most studies, only one accelerating stress variable is used. Sometimes accelerating one stress variable does not yield enough failure data. Thus, two stress variables may be needed for additional acceleration. In this paper, two stress variables are considered. The inclusion of two stress variables in a test design will lead to a better understanding of the effect of two simultaneously operating stress variables. Also, the author assumes that the failure time of the test units follows a GE distribution. It is observed that the GE distribution can be used quite effectively to analyze lifetime data in place of gamma, Weibull and log-normal distributions. Also, most studies in this field have focused on the derivation of optimum test plans. In this paper, the author examined the estimation of model parameters and the optimization of the test design. In this paper, the asymptotic and bootstrap CIs for the model parameters are calculated. In addition, a sensitivity analysis is performed to examine the effect of the changes in the pre-estimated parameters on the optimal hold times. For determining the optimal test plan, due to nonlinearity and complexity of the objective function, the particle swarm optimization (PSO) algorithm is developed to calculate the optimal hold times. In this method, the research speed is very fast and optimization ability is more.

scholarly journals Optimum Time-Censored Constant-Stress PALTSP for the Burr Type XII Distribution Using Tampered Failure Rate Model

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
P. W. Srivastava ◽  
D. Sharma
Keyword(s):  
Asymptotic Variance ◽  
Constant Stress ◽  
Accelerated Life Test ◽  
Rate Model ◽  
Life Test ◽  
Test Statistic ◽  
Optimum Time ◽  
Optimal Plan ◽  
Accelerated Life ◽  
Burr Type Xii

This paper presents optimum design of time-censored constant-stress partially accelerated life test sampling plan (PALTSP) in which each item runs either at use or at accelerated conditions and product life follows Burr type XII. The optimal plan consists in finding out sample proportions allocated to both use and accelerated conditions by minimizing the asymptotic variance of test statistic for deciding on acceptance/rejection of the lot such that producer’s and consumer’s interests are safeguarded. The method developed has been illustrated using an example. Sensitivity analysis has also been carried out.

Time-dependent reliability analysis of harmonic drive based on transient FEA and accelerated life test

2020 ◽  
Vol 37 (7) ◽  
pp. 2293-2317 ◽  
Author(s):  
Xian Zhang ◽  
Gedong Jiang ◽  
Hao Zhang ◽  
Xialun Yun ◽  
Xuesong Mei
Keyword(s):  
Residual Strength ◽  
Accelerated Life Test ◽  
Time Dependent ◽  
Variable Load ◽  
Strength Model ◽  
Harmonic Drive ◽  
Life Test ◽  
Content Type ◽  
Accelerated Life ◽  
Reliability Method

Purpose The purpose of this paper is to analyze the time-dependent reliability of harmonic drive. Design/methodology/approach The transient finite element analysis (FEA) of harmonic drive is established to calculate the stress under different loads. Combined with the residual strength model and random variables, the time-dependent reliability model of harmonic drive is deduced by the stochastic perturbation method and Edgeworth series. Based on accelerated life tests, the degradation parameters are estimated by maximizing likelihood function. Under variable load, the key stress from transient FEA is transformed into probability density function by kernel density estimation, and the residual strength model is modified by adding adjustment factors to deal with strength degradation under different loads. Findings The critical position of stress concentration from transient FEA is consistent with the fatigue fracture position at the accelerated life test sample. Compared with the time-dependent reliability method with equivalent circular-shell static stress or empirical degradation parameters, the proposed method has the smallest prediction error of failure life. Under variable load, the state function should be expanded to second-order series for avoiding error items relevant to variance. The failure life expectation under random variable load is smaller than that under constant load. Originality/value The time-dependent reliability method of harmonic drive is firstly proposed under constant and variable load. The transient FEA of harmonic drive is established to calculate the stress for strength analysis. The accelerated life test of harmonic drive is conducted for degradation parameters estimation. The adjustment factor is added to the residual strength model for strength degradation under different loads.

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