Incomplete Block Designs (Lecture Notes in Statistics,Vol. l)

Because mixtures of exponential distributions (with constant failure rate) have the decreasing failure rate (DFR) property, as shown by Proschan in the sixties, it is not unexpected that mixtures of distributions that have a mildly increasing failure rate (IFR) also have this property. What is. perhaps, surprising is that mixtures of IFR distributions with rapidly increasing failure rate may also behave in this manner. Two striking examples of such mixtures are presented here and illustrated graphically. This phenomenon could be the cause of concern, in practice, when it is suspected that a sample is based on pooled data.     

Selected tables in Mathematical Statistics,Vol. 3.

This article demonstrates advantages of using nonorthogonal resolution IV designs for running small screening experiments when the primary goal is identification of important main effects (MEs) with a secondary goal of entertaining a small number of potentially important second-order interactions. This is accomplished by evaluating the structure and performance of designs obtained by folding over small efficient nonorthogonal resolution III designs and comparing them with more commonly used orthogonal resolution III designs of comparable size, such as fractional factorials and Plackett–Burman designs. The folded-over designs are available for a wider class of run sizes and perform as well as or better than resolution III competitors in selecting the correct model when a few active two-factor interactions are present and significantly outperform resolution III competitors in terms of correctly identifying MEs. A simple two-step procedure is proposed for analyzing data from such designs that separates the goals and is well suited for sorting through likely models quickly.     

Reliability Estimation of the Pultrusion Process Using the First-Order Reliability Method (FORM)

In the present study the reliability estimation of the pultrusion process of a flat plate is analyzed by using the first order reliability method (FORM). The implementation of the numerical process model is validated by comparing the deterministic temperature and cure degree profiles with corresponding analyses in the literature. The centerline degree of cure at the exit (CDOCE) being less than a critical value and the maximum composite temperature (T _max) during the process being greater than a critical temperature are selected as the limit state functions (LSFs) for the FORM. The cumulative distribution functions of the CDOCE and T _max as well as the correlation coefficients are obtained by using the FORM and the results are compared with corresponding Monte-Carlo simulations (MCS). According to the results obtained from the FORM, an increase in the pulling speed yields an increase in the probability of T _max being greater than the resin degradation temperature. A similar trend is also seen for the probability of the CDOCE being less than 0.8.     

Author Index,Vol. 72 (1995)

Author index, vol. 74 (1995/96)