Papers by Keyword: Lifetime Distribution

Abstract: —This paper explores a new method to find most reliable lifetime distribution function of systems, via an applied heuristic model. In most operating systems which complicity of system obligates high degree of reliability, this model will be use to propose a more appropriate reliability function between lifetime distribution based and another that is based on relevant Extreme Value distribution. A numeric study will be reviewed to clear the concepts of this paper.

Abstract: The structure of isotactic polypropylene (PP) and its blends with ethylene-propylene-diene terpolymer EPDM (0-100%) containing the unvulcanized and the vulcanized rubber phase were studied using positron annihilation lifetime (PAL) spectroscopy technique and thermostimulated luminescence (TSL). Cross-linking in the polymer blends is one of the effective ways to create novel materials with effective industrial properties. Meanwhile, composition of such systems is very complicated since it contains microphases of the dispersed components, cross-linked or not, elements of the cross-linking agents, which have some distribution between the blend components. This distribution, heterogeneity and also variation of elementary free volumes due to cross-linking are the points of interest in the study of polymer blend structures.

Abstract: Pitting corrosion damages seriously the structure strength of port facilities. To estimate the lifetime of port facilities, a new lifetime distribution model of port facilities with pitting corrosion of stochastic processes is proposed. Pitting corrosion can be considered as a combination of two physical processes: pit initiation process and pit growth process. The pit generation process is modeled as a non homogeneous Poisson process. The pit growth process is represented by a gamma process. A lifetime distribution model is derived based on the combined stochastic processes. Finally the proposed models are tested and simulated. The results indicate that the proposed model is feasible and valid for estimating the lifetime of port facilities.

Abstract: Reliability of products has long been considered as an important quality characteristic. Traditional methods of product reliability assessment are based on lifetime data. With products being much more reliable and the growing need for developing new products within shorter period and at lower cost, we can hardly get enough lifetime data in many cases. Performance degradation data can also be used for reliability assessment. Recently, they are found to be useful in some cases where they are easier to collect. But when performance degradation data are also limited and some lifetime data are available, it is preferred to utilize both information sources. This paper deals with the problem of reliability assessment combining both performance degradation data and lifetime data. It is assumed that two samples from the same product are tested differently. Degradation data are collected from one sample and lifetime data from the other. First, the performance degradation model is established, using either statistical methods or methods from physics of failure. Then lifetime of the product, which is defined as the first time when the performance crosses the known failure threshold, is calculated. The MLE method is used for parameter estimation where the maximum likelihood function is multiplication of the one from degradation data and the one from lifetime data. To illustrate the proposed method, an example of the metallized film capacitor, which is used in inertial confinement fusion (ICF) facility, is given. We model the performance degradation data of metallized film capacitor with Wiener process with drift. The failure of the capacitor is defined as the first time when its capacitance drops below a threshold. The lifetime distribution is deduced and the parameters are estimated from the joint maximum likelihood function. A comparison is conducted between the assessment results of degradation data only and those of combination of degradation data and lifetime data. In conclusion we propose that both degradation information and lifetime information should be used when neither of them is sufficient enough for reliability assessment. Some directions for future work are also discussed.