Statistical analysis of dependent competing risks model in constant stress accelerated life testing with progressive censoring based on copula function

In this paper, we consider the statistical analysis for the dependent competing risks model in theconstant stress accelerated life testing (CSALT) with Type-II progressive censoring. It is focusedon two competing risks from Lomax distribution. The maximum likelihood estimators of theunknown parameters, the acceleration coefficients and the reliability of unit are obtained by usingthe 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 byusing Bootstrap-p and Bootstrap-t method. Then, a simulation study is carried out by the MonteCarlo method for different measures of Kendall’s tau and different testing schemes. Finally, a realcompeting risks data is analysed for illustrative purposes. The results indicate that using copulafunction to deal with the dependent competing risks problems is effective and feasible.

STATISTICAL INFERENCE OF WEIBULL DISTRIBUTION FOR TAMPERED FAILURE RATE MODEL IN PROGRESSIVE STRESS ACCELERATED LIFE TESTING

In this note,the tampered failure rate model is generalized from the step-stress accelerated life testing setting to the progressive stress accelerated life testing for the first time.For the parametric setting where the scale parameter satisfying the equation of the inverse power law is Weibull,maximum likelihood estimation is investigated.

Parameter Estimation Based on Censored Data under Partially Accelerated Life Testing for Hybrid Systems due to Unknown Failure Causes

In general,simple subsystems like series or parallel are integrated to produce a complex hybrid system.The reliability of a system is determined by the reliability of its constituent components.It is often extremely difficult or impossible to get specific information about the component that caused the system to fail.Unknown failure causes are instances in which the actual cause of systemfailure is unknown.On the other side,thanks to current advanced technology based on computers,automation,and simulation,products have become incredibly dependable and trustworthy,and as a result,obtaining failure data for testing such exceptionally reliable items have become a very costly and time-consuming procedure.Therefore,because of its capacity to produce rapid and adequate failure data in a short period of time,accelerated life testing(ALT)is the most utilized approach in the field of product reliability and life testing.Based on progressively hybrid censored(PrHC)data froma three-component parallel series hybrid system that failed to owe to unknown causes,this paper investigates a challenging problem of parameter estimation and reliability assessment under a step stress partially accelerated life-test(SSPALT).Failures of components are considered to follow a power linear hazard rate(PLHR),which can be used when the failure rate displays linear,decreasing,increasing or bathtub failure patterns.The Tempered random variable(TRV)model is considered to reflect the effect of the high stress level used to induce early failure data.The maximum likelihood estimation(MLE)approach is used to estimate the parameters of the PLHR distribution and the acceleration factor.A variance covariance matrix(VCM)is then obtained to construct the approximate confidence intervals(ACIs).In addition,studentized bootstrap confidence intervals(ST-B CIs)are also constructed and compared with ACIs in terms of their respective interval lengths(ILs).Moreover,a simulation study is conducted to demonstrate the performance of the estimation procedures and the methodology discussed in this paper.Finally,real failure data from the air conditioning systems of an airplane is used to illustrate further the performance of the suggested estimation technique.

Detonator stepping stress acceleration life test

Through the failure mechanism analysi s and simulation test of a certain kind of detonator,this paper confirms the str ess level of the stepping stress acceleration life test of the detonator,and t hen e stablishes the data processing mathematical model and storage life forecasting m ethod.At last,according to the result of the stepping stress acceleration lif e test of the detonator,this paper forecasts the reliable storage life of the detonator under the normal stress level.

Research of Step-down Stress Accelerated Degradation Data Assessment Method of a Certain Type of Missile Tank

The performance degradation rates of the missile tank are generally time-varying functions uneasily evaluated by general classical evaluation methods. This paper develops a segmented nonlinear accelerated degradation model （SNADM） based on the equivalent method of accumulative damage theory, which tackles the problem that product life is difficult to be determined with degradation rate being a function of the variable of time. A segmented expression of the function of population accumulative degradation is derived. And combined with nonlinear function, an accelerated degradation function, i.e., SNADM is obtained. The parameters of the SNADM are identified by numerical iteration, and the statistical function of degradation track is extrapolated. The reliability function is determined through the type of random process of the degradation distribution. Then an evaluation of product storage life is undertaken by combining the statistical function of degradation track, reliability function and threshold. An example of a missile tank undergoes a step-down stress accelerated degradation test （SDSADT）, in which the results with the SNADM and the classical method are evaluated and compared. The technology introduced is validated with the resultant coincidence of both evaluated and field storage lives.