Reliability Modeling of Dependent Competitive Failure with Continuous Degradation and Random Shocks

2021 ◽  
Author(s):  
Jialin Ma ◽  
Guo Xie ◽  
Lingxia Mu ◽  
Jing Xin ◽  
Wenbin Chen ◽  
...  
Keyword(s):  
Reliability Modeling ◽  
Random Shocks

scholarly journals Reliability modeling for competing failure systems with instant-shift hard failure threshold

2018 ◽  
Vol 42 (4) ◽  
pp. 457-467 ◽  
Author(s):  
Jingyi Liu ◽  
Yugang Zhang ◽  
Bifeng Song
Keyword(s):  
Sensitivity Analysis ◽  
System Reliability ◽  
Reliability Model ◽  
External Shocks ◽  
Reliability Modeling ◽  
Soft Failure ◽  
Random Shock ◽  
Hard Failure ◽  
Engineering Practices ◽  
Random Shocks

Many researchers have modeled systems under multiple dependent competing failure processes (MDCFP) in recent years. Typically, those failure processes consist of degradation (soft failure) and random shock (hard failure). In previous papers the threshold of hard failure has been a fixed value, which does not reflect engineering practices. Threshold refers to the ability to resist external random shocks, which shifts with time as the system is used. Thus, this paper establishes a model for MDCFP with instant-shift hard threshold. The hard failure threshold changes with time instantaneously, and it is also influenced by external shocks. This paper also presents a system reliability model. The effectiveness of the presented model is demonstrated by a reliability analysis of the micro-engine at Sandia National Laboratories. In addition, a sensitivity analysis is performed for specific parameters.

scholarly journals Reliability Modeling for Humidity Sensors Subject to Multiple Dependent Competing Failure Processes with Self-Recovery

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2714 ◽  
Author(s):  
Jia Qi ◽  
Zhen Zhou ◽  
Chenchen Niu ◽  
Chunyu Wang ◽  
Juan Wu
Keyword(s):  
Reliability Model ◽  
Humidity Sensors ◽  
Reliability Modeling ◽  
Reliability Models ◽  
Soft Failure ◽  
Recent Developments ◽  
General Reliability ◽  
Hard Failure ◽  
Mechanism Of Failure ◽  
Random Shocks

Recent developments in humidity sensors have heightened the need for reliability. Seeing as many products such as humidity sensors experience multiple dependent competing failure processes (MDCFPs) with self-recovery, this paper proposes a new general reliability model. Previous research into MDCFPs has primarily focused on the processes of degradation and random shocks, which are appropriate for most products. However, the existing reliability models for MDCFPs cannot fully characterize the failure processes of products such as humidity sensors with significant self-recovery, leading to an underestimation of reliability. In this paper, the effect of self-recovery on degradation was analyzed using a conditional probability. A reliability model for soft failure with self-recovery was obtained. Then, combined with the model of hard failure due to random shocks, a general reliability model with self-recovery was established. Finally, reliability tests of the humidity sensors were presented to verify the proposed reliability model. Reliability modeling for products subject to MDCFPs with considering self-recovery can provide a better understanding of the mechanism of failure and offer an alternative method to predict the reliability of products.

Method for the reliability modeling of selfrepairing onboard information systems

1998 ◽  
Vol 4 (4) ◽  
pp. 55-60
Author(s):  
B.A. Mandziy ◽  
◽  
V.P. Belyaev ◽  
B.Yu. Volotchiy ◽  
◽  
...  
Keyword(s):  
Information Systems ◽  
Reliability Modeling

Nonlinear Dynamics and Chaos: Application to Financial Markets in Pakistan

1994 ◽  
Vol 33 (4II) ◽  
pp. 1417-1429 ◽  
Author(s):  
Nasir M. Khiui
Keyword(s):  
Financial Markets ◽  
Chaotic Dynamics ◽  
Ad Hoc ◽  
Linear Models ◽  
Brain Research ◽  
Economic Data ◽  
Differential Equation Models ◽  
Short Run ◽  
The Business Cycle ◽  
Random Shocks

Recently there has been an increased interest in the theory of chaos by macroeconomists and fmancial economists. Originating in the natural sciences, applications of the theory have spread through various fields including brain research, optics, metereology, and economics. The attractiveness of chaotic dynamics is its ability to generate large movements which appear to be random, with greater frequency than linear models. Two of the most striking features of any macro-economic data are its random-like appearance and its seemingly cyclical character. Cycles in economic data have often been noticed, from short-run business cycles, to 50 years Kodratiev waves. There have been many attempts to explain them, e.g. Lucas (1975), who argues that random shocks combined with various lags can give rise to phenomena which have the appearance of cycles, and Samuelson (1939) who uses the familiar multiplier accelerator model. The advantage of using non-linear difference (or differential) equation models to explain the business cycle is that it does not have to rely on ad hoc unexplained exogenous random shocks.

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