Approximate interval estimates for mechanical reliability

Download
Author
Yang, Wen-Huei
Date
1990-09Advisor
Woods, W.M.
Second Reader
Bailey, Michael
Metadata
Show full item recordAbstract
Two approximate interval estimation procedures for mechanical component reliability, P(XY), are developed and their accuracy evaluated by computer simulations. The strength, X, of the component and the stress, Y, applied to it are independent normally distributed variables with unknown means and variances. In the first interval procedure the variances are equal. In the second procedure the variances may be unequal. The derived intervals are quite accurate for the cases simulated which include large and small sample sizes. These procedures are simple to apply and require the use of percentile points of the Student's distribution. In the second procedure, the degrees of freedom of the associated t statistic is a function of the test data, and therefore it is random.
Rights
Copyright is reserved by the copryright owner.Collections
Related items
Showing items related by title, author, creator and subject.
-
A note on generating multivariate data with desired means, variances, and covariances
Capra, J.R.; Elster, R.S. (1971);A method is shown for creating a set of ɳ observations on Ƥ variables, with the p variables having specified means, variances, and covariances. This method differs from previous techniques in that it uses Crout factorization ... -
Controlling the influences of component variables
Elster, Richard S. (Monterey, California. Naval Postgraduate School, 1972-05); NPS-55Ea72051AIn the comparison of military units or systems, many attributes including performance, might be measured. One general approach to determining 2which system is best involves forming a composite measure of the differentially ... -
On a Stochastic Knapsack Problem and Generalizations
Morton, D.P.; Wood, R.K. (1998);We consider an integer stochastic knapsack problem (SKP) where the weight of each item is deterministic, but the vector of returns for the items is random with known distribution. The objective is to maximize the probability ...