Comparison of Weibull Distribution and Crow-AMSAA Model Used in Cable Failure Analysis

Author(s):  
Zeyang Tang ◽  
Wenjun Zhou ◽  
Jianhui Yu ◽  
Chengke Zhou
2013 ◽  
Vol 378 ◽  
pp. 61-64 ◽  
Author(s):  
Ting Peng ◽  
Xiao Ling Wang ◽  
Shuan Fa Chen

The Weibull distribution is an ideal model for failure analysis. In this work, it is applied to simulate pavement performance regression process. Then, pavement performance prediction model is constructed according to the Weibull distribution. Historical pavement performance data are used to evaluate the practical performance of the model. According to the experimental results, ideal performance is obtained. It provides more accurate results compared with the previous work.


2014 ◽  
Vol 492 ◽  
pp. 574-578 ◽  
Author(s):  
Razika Ihaddadene ◽  
Nabila Ihaddadene ◽  
Merouane Mostefaoui

Three kinds of methods commonly used for estimating Weibull parameters were fitted to a collection of wind speed data at 10 m above ground level for the year of 2009 to determine the best distribution function which describes the wind speed variation at Msila, Algeria site for wind energy. Three methods used the coefficient of determination R2, root mean square error RMSE and Chi-Square χ2 were compared with failure analysis. According to the results of failure analysis the moment method has better results than graphic method and power density method. The wind power density calculated from moment method shows a good approximation to estimate the power density. So the Weibull distribution using the moment method adequately fit the data and it is suitable for modeling the wind speed distribution in Msila province of Algeria.


1986 ◽  
Vol 23 (04) ◽  
pp. 893-903 ◽  
Author(s):  
Michael L. Wenocur

Brownian motion subject to a quadratic killing rate and its connection with the Weibull distribution is analyzed. The distribution obtained for the process killing time significantly generalizes the Weibull. The derivation involves the use of the Karhunen–Loève expansion for Brownian motion, special function theory, and the calculus of residues.


Author(s):  
John R. Devaney

Occasionally in history, an event may occur which has a profound influence on a technology. Such an event occurred when the scanning electron microscope became commercially available to industry in the mid 60's. Semiconductors were being increasingly used in high-reliability space and military applications both because of their small volume but, also, because of their inherent reliability. However, they did fail, both early in life and sometimes in middle or old age. Why they failed and how to prevent failure or prolong “useful life” was a worry which resulted in a blossoming of sophisticated failure analysis laboratories across the country. By 1966, the ability to build small structure integrated circuits was forging well ahead of techniques available to dissect and analyze these same failures. The arrival of the scanning electron microscope gave these analysts a new insight into failure mechanisms.


Author(s):  
Evelyn R. Ackerman ◽  
Gary D. Burnett

Advancements in state of the art high density Head/Disk retrieval systems has increased the demand for sophisticated failure analysis methods. From 1968 to 1974 the emphasis was on the number of tracks per inch. (TPI) ranging from 100 to 400 as summarized in Table 1. This emphasis shifted with the increase in densities to include the number of bits per inch (BPI). A bit is formed by magnetizing the Fe203 particles of the media in one direction and allowing magnetic heads to recognize specific data patterns. From 1977 to 1986 the tracks per inch increased from 470 to 1400 corresponding to an increase from 6300 to 10,800 bits per inch respectively. Due to the reduction in the bit and track sizes, build and operating environments of systems have become critical factors in media reliability.Using the Ferrofluid pattern developing technique, the scanning electron microscope can be a valuable diagnostic tool in the examination of failure sites on disks.


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