Tampered random variable modeling for multiple step-stress life test

Author(s):  
Farha Sultana ◽  
Anup Dewanji
2018 ◽  
Vol 7 (3.31) ◽  
pp. 136
Author(s):  
G Prasad ◽  
R Subba Rao ◽  
R R.L. Kantam

A combination of Pareto and Rayleigh distributions considered for a new T-X probability model named as Pareto-Rayleigh distribution (PR distribution). We have chosen a life time random variable X from PR distribution whose lots are to be decided for acceptance or otherwise based on sample lifetimes drawn from the lot.  A sampling scheme is developed in such way that the sample is divided into different groups and experiment is terminated whenever the first failure noticed in each group.  The theory of ordered statistics is applied for the criterion of acceptance and is compared with the similar works proposed by other authors.  


Author(s):  
Y. Pan

The D defect, which causes the degradation of gate oxide integrities (GOI), can be revealed by Secco etching as flow pattern defect (FPD) in both float zone (FZ) and Czochralski (Cz) silicon crystal or as crystal originated particles (COP) by a multiple-step SC-1 cleaning process. By decreasing the crystal growth rate or high temperature annealing, the FPD density can be reduced, while the D defectsize increased. During the etching, the FPD surface density and etch pit size (FPD #1) increased withthe etch depth, while the wedge shaped contours do not change their positions and curvatures (FIG.l).In this paper, with atomic force microscopy (AFM), a simple model for FPD morphology by non-crystallographic preferential etching, such as Secco etching, was established.One sample wafer (FPD #2) was Secco etched with surface removed by 4 μm (FIG.2). The cross section view shows the FPD has a circular saucer pit and the wedge contours are actually the side surfaces of a terrace structure with very small slopes. Note that the scale in z direction is purposely enhanced in the AFM images. The pit dimensions are listed in TABLE 1.


1998 ◽  
Vol 37 (03) ◽  
pp. 235-238 ◽  
Author(s):  
M. El-Taha ◽  
D. E. Clark

AbstractA Logistic-Normal random variable (Y) is obtained from a Normal random variable (X) by the relation Y = (ex)/(1 + ex). In Monte-Carlo analysis of decision trees, Logistic-Normal random variates may be used to model the branching probabilities. In some cases, the probabilities to be modeled may not be independent, and a method for generating correlated Logistic-Normal random variates would be useful. A technique for generating correlated Normal random variates has been previously described. Using Taylor Series approximations and the algebraic definitions of variance and covariance, we describe methods for estimating the means, variances, and covariances of Normal random variates which, after translation using the above formula, will result in Logistic-Normal random variates having approximately the desired means, variances, and covariances. Multiple simulations of the method using the Mathematica computer algebra system show satisfactory agreement with the theoretical results.


2018 ◽  
Vol 18 (3) ◽  
pp. 260-270
Author(s):  
Bosik Kang ◽  
Yongbum Lee ◽  
Dongsoo Jung ◽  
Chungsung Lee
Keyword(s):  

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