scholarly journals An E-Bayesian method for reliability analysis of exponentially distributed products with zero-failure data

2016 ◽  
Vol 18 (03) ◽  
pp. 445-449 ◽  
Author(s):  
Yi-Chao Yin ◽  
Hong-Zhong Huang ◽  
Weiwen Peng ◽  
Yan-Feng Li ◽  
Jinhua Mi
Keyword(s):  
Reliability Analysis ◽  
Bayesian Method ◽  
Failure Data

Reliability Analysis of Vehicle Equipment Based on Bayesian Method

2012 ◽  
Vol 253-255 ◽  
pp. 2091-2096
Author(s):  
Yan Feng Tang ◽  
Hui Mei Li ◽  
Xiang Kai Liu ◽  
Shao Qing Liu
Keyword(s):  
Parameter Estimation ◽  
Data Processing ◽  
Reliability Analysis ◽  
Bayesian Method ◽  
Distribution Model ◽  
Optimal Distribution ◽  
Model Based ◽  
Selection Of

Bayesian method was introduced and leaded into the vehicle fault data processing. The parameter estimation and the selection of the optimal distribution model based on Bayesian method were studied, and an example was given. The references are provided for the application of Bayesian method in the large complicated systems, such as vehicle equipments.

Life cycle reliability analysis using imprecise failure data

2017 ◽  
Vol 6 (4) ◽  
pp. 265-275
Author(s):  
Subrata Bera ◽  
D. Datta ◽  
Avinash J. Gaikwad
Keyword(s):  
Life Cycle ◽  
Reliability Analysis ◽  
Failure Data

Effect of Model Error on Reliability Analysis of Surface Cracks

2018 ◽  
Author(s):  
Mahmoud Ibrahim ◽  
Karmun Doucette ◽  
Sherif Hassanien ◽  
Doug Langer
Keyword(s):  
Reliability Analysis ◽  
Structural Integrity ◽  
Service Failure ◽  
Epistemic Uncertainty ◽  
Model Error ◽  
Management Program ◽  
Quantitative Risk Assessment ◽  
Normal Operation ◽  
Pipeline System ◽  
Failure Data

The application of reliability-based structural integrity enables the process of quantitative risk assessment as part of pipelines’ integrity management program (IMP). This paper explores two topics that present challenges in terms of the practical adoption of a reliability-based IMP. The first challenge is the balance between perceived and true risk when implementing a quantitative reliability-based integrity model. This is a cornerstone for building stakeholder confidence in the calculated probability of failure (PoF) which is applied to safety and economically driven integrity decisions. The second challenge is the assurance that all relevant sources of uncertainty have been incorporated, which is essential for ensuring an accurate representation of the risk of failure of the pipeline. The level of conservatism (i.e. sufficient margin of error to maintain safety) incorporated when addressing these challenges may create a situation where calculated PoFs become inflated; becoming disproportionate to the failure history and contradictory to the current safe operation of pipelines being modeled. Two different PoF calibration approaches are proposed as practical options to address these challenges. The first method calibrates model error using an operator’s in-service failure history (i.e. failures that occurred under normal operation). The second method uses a set of failure data (including hydrostatic test failures and in-service failures) as selected by the operator considering key factors to ensure adequate representation of their specific pipeline system. These options will be demonstrated by assessing the integrity reliability of a hypothetical pipeline system. This work is expected to help evaluate the feasibility of challenging current practices regarding practical inclusion of epistemic uncertainty in integrity reliability analysis of pipelines.

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