Application of Stochastic Optimization to Optimal Preventive Maintenance Problem

The contribution deals with the optimization of a sequential preventive maintenance schedule of a technical device. We are given an initial time-to-failure probability distribution, model of changes of this distribution after maintenance actions, as well as the costs of maintenance, of a device acquisition, and of the impact of failure. The maintenance timing and, eventually, its extent, are the matter of optimization. The objective of the contribution is two-fold: first, to formulate a proper (random) objective function evaluating the lifetime of the maintained device relatively to maintenance costs;second, to propose a numerical method searching for a maintenance policy optimizing selected characteristics of this objective function. The method is based on the MCMC random search combined with simulated annealing. It is also shown that such a method is rather universal for different problem specifications. The approach will be illustrated on an artificial example dealing with accelerated lifetime after each maintenance action.

Lifetime prediction based on Gamma processes from accelerated degradation data

Accelerated degradation test is a useful approach to predict the product lifetime at the normal use stress level, especially for highly reliable products. Two kinds of the lifetime prediction based on Gamma processes were studied. One was to predict the lifetime of the population from accelerated degradation data, and the other was to predict the lifetime of an individual by taking the accelerated degradation data as prior information. For an extensive application, the Gamma process with a time transformation and random effects was considered. A novel contribution is that a deducing method for determining the relationships between the shape and scale parameters of Gamma processes and accelerated stresses was presented. When predicting the lifetime of an individual, Bayesian inference methods were adopted to improve the prediction accuracy, in which the conjugate prior distribution and the non-conjugate prior distribution of random parameters were studied. The conjugate prior distribution only considers the random effect of the scale parameter while the non-conjugate prior distribution considers the random effects of both the scale and shape parameter. The application and usefulness of the proposed method was demonstrated by the accelerated degradation data of carbon-film resistors.

Lifetime prediction of electrical connectors under multiple environment stresses of temperature and particulate contamination

Electrical connectors play a significant role in the electronic and communication systems. As they are often exposed in the atmosphere environment, it is extremely easy for them to cause electrical contact failure. It is essential to carry out the reliability modeling and predict the lifetime. In the present work, the accelerated lifetime testing method which is on account of the uniform design method was designed to obtain the degradation data under multiple environmental stresses of temperature and particulate contamination for electrical connectors. Based on the degradation data, the pseudo life can be acquired. Then the reliability model was established by analyzing the pseudo life. Accordingly, the reliability function and reliable lifetime function were set up, and the reliable lifetime of the connectors under the multiple environment stresses of temperature and particulate contamination could be predicted for electrical connectors,

Rapid evaluation method for the normal lifetime of an infrared light-emitting diode

Based on the Arrhenius model, a rapid evaluation method for an infrared diode＇s normal lifetime is proposed, and the theoretical model is constructed. Accelerated life testing of an infrared light-emitting diode （IRLED）, which takes less time than usual, is carried out under temperature and electric current stress. Using this method, the activation energy and the IRLED＇s normal lifetime are calculated and analyzed. Key words： Arrhenius model; acceleration lifetime test; IRLED; activation energy

The expression correction of transistor current gain and its application in reliability assessment

Considering the impacts of ideal factor n, VBE and band gap changes with the temperature on current gain, the current gain expression has been corrected to make the results closer to the actual test. Besides, the accelerating lifetime study method in the constant temperature-humidity stress is used to estimate the reliability of the same batch transistors. Applying the revised findings from the expression, the current gains before and after the test are compared and analyzed, and, according to the degradation data of the current gain, the transistor lifetimes in the test stress are respectively extrapolated in the different failure criteria.

Statistical Inference for a Simple Step Stress Model with Competing Risks Based on Generalized Type-ⅠHybrid Censoring

This paper investigates a simple step-stress accelerated lifetime test(SSALT)model for the inferential analysis of exponential competing risks data.A generalized type-I hybrid censoring scheme is employed to improve the efficiency and controllability of the test.Firstly,the MLEs for parameters are established based on the cumulative exposure model(CEM).Then the conditional moment generating function(MGF)for unknown parameters is set up using conditional expectation and multiple integral techniques.Thirdly,confidence intervals(CIs)are constructed by the exact MGF-based method,the approximate normality-based method,and the bias-corrected and accelerated(BCa)percentile bootstrap method.Finally,we present simulation studies and an illustrative example to compare the performances of different methods.