In this paper, testing exponentiality against new better than used in convex average and denote by (NBUCA), or its dual (NWUCA) is investigated through the U-test. The percentiles of these tests are tabulated for samples sizes n = 5(1)40. The power estimates of the test are simulated for some commonly used distributions in reliability. Pitman's asymptotic efficiency of the test is calculated and compared. Data of 40 patients suffering from blood cancer disease (Leukemia) is considered as a practical application of the proposed test in the medical sciences.

Posbist reliability of typical systems is preliminarily discussed in Cai (1991). In this paper, we focus on the posbist reliability analysis of some typical systems in depth. First, the lifetime of the system is dealt as a fuzzy variable defined on the possibility space (U, ${\phi}$, $P_{oss}$) and the universe of discourse is expanded from (0, $+{\infty}$) to ($-{\infty},\;+{\infty}$). Then, a concrete possibility distribution function of the fuzzy variable is given, i.e., a Gaussian fuzzy variable. Finally, posbist reliability of typical systems (series, parallel, series-parallel, parallel-series, cold redundant system) is deduced. The expansion makes the proofs of some theorems straightforward and allows us to easily obtain the posbist reliability of typical systems. To illustrate the method a numerical example is given.

Wood-plastic composites (WPC) are gaining market share in the building industry because of durability/maintenance advantages of WPC over traditional wood products and because of the removal of chromated copper arsenate (CCA) pressure-treated wood from the market. In order to ensure continued market share growth, WPC manufacturers need greater focus on reliability, quality, and cost. The reliability methods outlined in this paper can be used to improve the quality of WPC and lower manufacturing costs by reducing raw material inputs and minimizing WPC waste. Statistical methods are described for analyzing stiffness (tangent modulus of elasticity: MOE) and flexural strength (modulus of rupture: MOR) test results on sampled WPC panels. Descriptive statistics, graphs, and reliability plots from these test data are presented and interpreted. Sources of variability in the MOE and MOR of WPC are suggested. The methods outlined may directly benefit WPC manufacturers through a better understanding of strength and stiffness measures, which can lead to process improvements and, ultimately, a superior WPC product with improved reliability, thereby creating greater customer satisfaction.

In this note, some comments concerning the testing procedures for the problems of stochastic comparison, testing IFR and testing NBU ageing properties are presented showing that the tests proposed in Belzunce, Candel and Ruiz(1998) are cumbersome to calculate and do not have as good asymptotic Pittman efficacies as simpler others already in the literature. This is done via new presentations of the measures on which Belzunce et al. base their tests.

There is a growing trend for asset intensive industries to outsource maintenance services of their complex assets since outsourcing through service contract reduces upfront investments in infrastructure, expertise and specialised maintenance facilities. Estimation of costs for such contracts is complex and it is important to the user and the service providers for economic variability. The service provider's profit is influenced by many factors such as the terms of the contract, reliability of asset, and the servicing strategies, costs of resources needed to carryout maintenance. There is a need to develop mathematical models for understanding future costs to build it into the contract price. Three policies for service contracts are proposed in this paper considering the concepts of outsourcing maintenance service of assets to the service providers. Conceptual models are developed for estimating servicing costs of outsourcing through service contracts by considering time dependent failure mode.

This paper presents estimations of the generalized Rayleigh distribution model based on grouped and censored data. The maximum likelihood method is used to derive point and asymptotic confidence estimates of the unknown parameters. The results obtained in this paper generalize some of those available in the literature. Finally, we test whether the current model fits a set of real data better than other models.