scholarly journals A Load Sharing System Reliability Model With Managed Component Degradation

2014 ◽  
Vol 63 (3) ◽  
pp. 721-730 ◽  
Author(s):  
Zhisheng Ye ◽  
Matthew Revie ◽  
Lesley Walls
2008 ◽  
Vol 44-46 ◽  
pp. 853-858 ◽  
Author(s):  
Guang Bo Hao ◽  
Li Yang Xie

As for load-sharing parallel system like multi-engine system and wire cable, dependence-failure must occur due to load redistributing, so the component life distributions changed. After the analysis of the disadvantage of failure probability equivalent principle and the transformation of equivalent working time of different life distribution based on damage equivalent principle, the parallel system reliability model applying full probability formula is established. The established reliability model provides a new method for reliability analysis of load-sharing parallel system whose component life follows any distribution.


2017 ◽  
Author(s):  
Askin Guler Yigitoglu ◽  
Thomas Harrison ◽  
Michael Scott Greenwood

Author(s):  
Sheng-Jia Ruan ◽  
Yan-Hui Lin

Standby redundancy can meet system safety requirements in industries with high reliability standards. To evaluate reliability of standby systems, failure dependency among components has to be considered especially when systems have load-sharing characteristics. In this paper, a reliability analysis and state transfer scheduling optimization framework is proposed for the load-sharing 1-out-of- N: G system equipped with M warm standby components and subject to continuous degradation process. First, the system reliability function considering multiple dependent components is derived in a recursive way. Then, a Monte Carlo method is developed and the closed Newton-Cotes quadrature rule is invoked for the system reliability quantification. Besides, likelihood functions are constructed based on the measurement information to estimate the model parameters of both active and standby components, whose degradation paths are modeled by the step-wise drifted Wiener processes. Finally, the system state transfer scheduling is optimized by the genetic algorithm to maximize the system reliability at mission time. The proposed methodology and its effectiveness are illustrated through a case study referring to a simplified aircraft hydraulic system.


2021 ◽  
Vol 11 (4) ◽  
pp. 1697
Author(s):  
Shi-Woei Lin ◽  
Tapiwa Blessing Matanhire ◽  
Yi-Ting Liu

While the dependence assumption among the components is naturally important in evaluating the reliability of a system, studies investigating the issues of aggregation errors in Bayesian reliability analyses have been focused mainly on systems with independent components. This study developed a copula-based Bayesian reliability model to formulate dependency between components of a parallel system and to estimate the failure rate of the system. In particular, we integrated Monte Carlo simulation and classification tree learning to identify key factors that affect the magnitude of errors in the estimation of posterior means of system reliability (for different Bayesian analysis approaches—aggregate analysis, disaggregate analysis, and simplified disaggregate analysis) to provide important guidelines for choosing the most appropriate approach for analyzing a model of products of a probability and a frequency for parallel systems with dependent components.


2011 ◽  
Vol 186 ◽  
pp. 499-504 ◽  
Author(s):  
Pan He ◽  
Jie Xu ◽  
Kai Gui Wu ◽  
Jun Hao Wen

Service-oriented workflows are the fundamental structures in service-oriented applications and changes in the workflow could cause dramatic changes in system reliability. In several ways to re-heal workflows in execution, re-sizing service pools in the workflow is practical and easy to implement. In order to quickly adjust to workflow or environmental changes, this paper presents a dynamic service pool size configuration mechanism from the point of view of maintaining workflow reliability. An architecture-based reliability model is used to evaluate the overall reliability of a workflow with service pools and an optimal method is proposed to get the combination of service pool size aiming at minimizing the sum of service pool size subject to the workflow reliability requirement. A case study is used to explain this method and experiment results show how to change service pool size to meet the workflow reliability requirements.


2018 ◽  
Vol 42 (4) ◽  
pp. 457-467 ◽  
Author(s):  
Jingyi Liu ◽  
Yugang Zhang ◽  
Bifeng Song

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.


2013 ◽  
Vol 365-366 ◽  
pp. 28-31
Author(s):  
Li Yang Xie ◽  
Wen Xue Qian ◽  
Ning Xiang Wu

Taking into account the uncertainty in material property and component quality, a complex mechanical component such as a gear should be treated as a series system instead of a component when evaluating its reliability, since there exist many sites of equal likelihood to fail. Besides, conventional system reliability model is not applicable to such a system because of the statistical dependence among the failures of the every element (damage site). The present paper presents a model to estimate complex mechanical component reliability by incorporating order statistic of element strength into load-strength interference analysis, which can deal with multiple failure mechanisms, reflect statistical dependence among element failure events and that among different failure modes.


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