A critique of the Reliability Analysis Center failure-rate-model for plastic encapsulated microcircuits

1998 ◽  
Vol 47 (2) ◽  
pp. 110-113 ◽  
Author(s):  
N. Sinnadurai ◽  
A.A. Shukla ◽  
M. Pecht
Keyword(s):  
Reliability Analysis ◽  
Failure Rate ◽  
Rate Model ◽  
Analysis Center

scholarly journals Reliability Analysis of Load-SharingK-out-of-NSystem Considering Component Degradation

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Chunbo Yang ◽  
Shengkui Zeng ◽  
Jianbin Guo
Keyword(s):  
Reliability Analysis ◽  
Failure Rate ◽  
Load Sharing ◽  
Performance Degradation ◽  
Random Component ◽  
Rate Model ◽  
Successful Operation ◽  
Degradation Model ◽  
System Requirement ◽  
Degradation Effect

TheK-out-of-Nconfiguration is a typical form of redundancy techniques to improve system reliability, where at leastK-out-of-Ncomponents must work for successful operation of system. When the components are degraded, more components are needed to meet the system requirement, which means that the value ofKhas to increase. The current reliability analysis methods overestimate the reliability, because using constantKignores the degradation effect. In a load-sharing system with degrading components, the workload shared on each surviving component will increase after a random component failure, resulting in higher failure rate and increased performance degradation rate. This paper proposes a method combining a tampered failure rate model with a performance degradation model to analyze the reliability of load-sharingK-out-of-Nsystem with degrading components. The proposed method considers the value ofKas a variable which is derived by the performance degradation model. Also, the load-sharing effect is evaluated by the tampered failure rate model. Monte-Carlo simulation procedure is used to estimate the discrete probability distribution ofK. The case of a solar panel is studied in this paper, and the result shows that the reliability considering component degradation is less than that ignoring component degradation.

Is high-altitude mountaineering Russian roulette?

2013 ◽  
Vol 9 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Edward K. Cheng
Keyword(s):  
High Altitude ◽  
Failure Rate ◽  
Rate Model ◽  
Reliability Engineering ◽  
Significant Difference ◽  
Inference Techniques ◽  
Decreasing Failure Rate

AbstractWhether the nature of the risks associated with climbing high-altitude (8000 m) peaks is in some sense “controllable” is a longstanding debate in the mountaineering community. Well-known mountaineers David Roberts and Ed Viesturs explore this issue in their recent memoirs. Roberts views the primary risks as “objective” or uncontrollable, whereas Viesturs maintains that experience and attention to safety can make a significant difference. This study sheds light on the Roberts-Viesturs debate using a comprehensive dataset of climbing on Nepalese Himalayan peaks. To test whether the data is consistent with a constant failure rate model (Roberts) or a decreasing failure rate model (Viesturs), it draws on Total Time on Test (TTT) plots from the reliability engineering literature and applies graphical inference techniques to them.

scholarly journals Probabilistic failure rate model of a tidal turbine pitch system

2020 ◽  
Vol 160 ◽  
pp. 987-997
Author(s):  
Fraser J. Ewing ◽  
Philipp R. Thies ◽  
Jonathan Shek ◽  
Claudio Bittencourt Ferreira
Keyword(s):  
Failure Rate ◽  
Rate Model ◽  
Tidal Turbine ◽  
Pitch System
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