Dependent Failure Modelling by Fault Tree Technique

Author(s):  
S. Contini
Keyword(s):  
2018 ◽  
Vol 6 (6) ◽  
pp. 24-34
Author(s):  
Irina N. KOLOSOK ◽  
◽  
Elena S. KORKINA ◽  
Alexandr V. TIKHONOV ◽  
◽  
...  

2019 ◽  
Vol 7 (2) ◽  
pp. 273-280
Author(s):  
Byeong Ho Cho ◽  
Wonki Hyun ◽  
Woojune Yi ◽  
Sang Ahm Kim
Keyword(s):  

Author(s):  
Clarence Rebello ◽  
Ted Kolasa ◽  
Parag Modi

Abstract During the search for the root cause of a board level failure, all aspects of the product must be revisited and investigated. These aspects encompass design, materials, and workmanship. In this discussion, the failure investigation involved an S-Band Power Amplifier assembly exhibiting abnormally low RF output power where initial troubleshooting did not provide a clear cause of failure. A detailed fault tree drove investigations that narrowed the focus to a few possible root causes. However, as the investigation progressed, multiple contributors were eventually discovered, some that were not initially considered.


1992 ◽  
Vol 26 (5-6) ◽  
pp. 1411-1420 ◽  
Author(s):  
S. H. Choudhury ◽  
S. L. Yu ◽  
Y. Y. Haimes

This paper presents an integrated methodology that allows determining the probability of noncompliance for a given wastewater treatment plant. The methodology applies fault-tree analysis, which uses failure probabilities of individual components, to predict the overall system failure probability. The methodology can be divided into two parts : risk identification and risk quantification. In risk identification, the key components in the system are determined by analyzing the contribution of individual component failures toward system failure (i.e., noncompliance). In risk quantification, a fault-tree model is constructed for the particular system, component failure probabilities are estimated, and the fault-tree model is evaluated to determine the probability of occurrence of the top event (i.e., noncompliance). A list can be developed that ranks critical events on the basis of their contributions to the probability of noncompliance. Such a ranking should assist managers to determine which components require most attention for a better performance of the entire system. A wastewater treatment plant for treating metal-bearing rinse water from an electroplating industry is used as an example to demonstrate the application of this methodology.


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