System‐Reliability Prediction in Impulsive‐Noise Environments, Based on Wear‐Dependent Failure Rates, Using Response “Peak” Statistics

1968 ◽  
Vol 43 (6) ◽  
pp. 1344-1350 ◽  
Author(s):  
T. I. Smits ◽  
R. F. Lambert
Keyword(s):  
System Reliability ◽  
Impulsive Noise ◽  
Reliability Prediction ◽  
Failure Rates ◽  
Response Peak ◽  
Dependent Failure

The Integrative Time-Dependent Modeling of the Reliability and Failure of the Causes of Drivers' Error Leading to Road Accidents

2015 ◽  
pp. 1279-1294
Author(s):  
Khashayar Hojjati-Emami ◽  
Balbir S. Dhillon ◽  
Kouroush Jenab
Keyword(s):  
Human Error ◽  
Time Dependent ◽  
Failure Rates ◽  
Road Accidents ◽  
Road Transportation ◽  
The Road ◽  
Representational Model ◽  
On The Road ◽  
The Moment ◽  
Dependent Failure

Nowadays, the human error is usually identified as the conclusive cause of investigations in road accidents. The human although is the person in control of vehicle until the moment of crash but it has to be understood that the human is under continued impact by various factors including road environment, vehicle and human's state, abilities and conduct. The current advances in design of vehicle and roads have been intended to provide drivers with extra comfort with less physical and mental efforts, whereas the fatigue imposed on driver is just being transformed from over-load fatigue to under-load fatigue and boredom. A representational model to illustrate the relationships between design and condition of vehicle and road as well as driver's condition and state on fatigue and the human error leading to accidents has been developed. Thereafter, the stochastic mathematical models based on time-dependent failure rates were developed to make prediction on the road transportation reliability and failure probabilities due to each cause (vehicle, road environment, human due to fatigue, and human due to non fatigue factors). Furthermore, the supportive assessment methodology and models to assess and predict the failure rates of driver due to each category of causes were developed and proposed.

Reliability Prediction for Offshore Renewable Energy: Data Driven Insights

2017 ◽  
Author(s):  
Fraser J. Ewing ◽  
Philipp R. Thies ◽  
Benson Waldron ◽  
Jonathan Shek ◽  
Michael Wilkinson
Keyword(s):  
Renewable Energy ◽  
Failure Rate ◽  
Reliability Assessment ◽  
Surrogate Data ◽  
Data Sources ◽  
Reliability Prediction ◽  
Failure Rates ◽  
Onshore Wind ◽  
Energy Devices ◽  
Frequency Converters

Accurately quantifying and assessing the reliability of Offshore Renewable Energy (ORE) devices is critical for the successful commercialisation of the industry. At present, due to the nascent stage of the industry and commercial sensitivities there is very little available reliability field data. This presents an issue: how can the reliability of ORE’s be accurately assessed and predicted with a lack of specific reliability data? ORE devices largely rely on the assessment of surrogate data sources for their reliability assessment. To date there are very few published studies that empirically assess the failure rates of offshore renewable energy devices [1]. The applicability of surrogate data sources to the ORE environment is critical and needs to be more thoroughly evaluated for a robust ORE device reliability assessment. This paper tests two commonly held assumptions used in the reliability assessment of ORE devices. Firstly, the constant failure rate assumption that underpins ORE component failure rate estimations is addressed. Secondly, a model that is often used to assess the reliability of onshore wind components, the Non-Homogeneous Poisson Power Law Process (PLP) model is empirically assessed and trend tested to determine its suitability for use in ORE reliability prediction. This paper suggests that pitch systems, generators and frequency converters cannot be considered to have constant failure rates when analysed via nonrepairable methods. Thus, when performing a reliability assessment of an ORE device using non-repairable surrogate data it cannot always be assumed that these components will exhibit random failures. Secondly, this paper suggests when using repairable system methods, the PLP model is not always accurate at describing the failure behaviour of onshore wind pitch systems, generators and frequency converters whether they are assessed as groups of turbines or individually. Thus, when performing a reliability assessment of an ORE device using repairable surrogate data both model choice and assumptions should be carefully considered.

An Efficient Methodology for the Reliability Analysis of Corroding Pipelines

2012 ◽  
Author(s):  
S. Zhang ◽  
W. Zhou
Keyword(s):  
System Reliability ◽  
Failure Modes ◽  
Weighting Factor ◽  
Probability Weighting ◽  
Index Method ◽  
First Order ◽  
Corrosion Defect ◽  
Small Leak ◽  
Reliability Method ◽  
Dependent Failure

This paper describes an efficient methodology that utilizes the first order reliability method (FORM) and system reliability approaches to evaluate the time-dependent failure probabilities of a pressurized pipeline at a single active corrosion defect considering three different failure modes, i.e. small leak, large leak and rupture. The criteria for distinguishing small leak, large leak and rupture at a given corrosion defect are established based on the information in the literature. The wedge integral and probability weighting factor methods are used to evaluate the probabilities of small leak and burst, whereas the conditional reliability index method is used to evaluate the probabilities of large leak and rupture. Two numerical examples are used to illustrate the accuracy, efficiency and robustness of the proposed methodology. The proposed methodology can be used to facilitate reliability-based corrosion management programs for energy pipelines.

System reliability prediction based on historical data

1990 ◽  
Vol 6 (3) ◽  
pp. 209-218 ◽  
Author(s):  
John S. Usher ◽  
Suraj M. Alexander ◽  
John D. Thompson
Keyword(s):  
System Reliability ◽  
Historical Data ◽  
Reliability Prediction

System Reliability Analysis With Dependent Component Failures During Early Design Stage—A Feasibility Study

2016 ◽  
Vol 138 (5) ◽  
Author(s):  
Yao Cheng ◽  
Xiaoping Du
Keyword(s):  
System Reliability ◽  
Reliability Prediction ◽  
Design Stage ◽  
Early Design ◽  
Early Design Stage ◽  
Design Concepts ◽  
Reliability Bounds ◽  
Lack Of Information ◽  
Dependent Component ◽  
Component Failures

It is desirable to predict product reliability accurately in the early design stage, but the lack of information usually leads to the use of independent component failure assumption. This assumption makes the system reliability prediction much easier, but may produce large errors since component failures are usually dependent after the components are put into use within a mechanical system. The bounds of the system reliability can be estimated, but are usually wide. The wide reliability bounds make it difficult to make decisions in evaluating and selecting design concepts, during the early design stage. This work demonstrates the feasibility of considering dependent component failures during the early design stage with a new methodology that makes the system reliability bounds much narrower. The following situation is addressed: the reliability of each component and the distribution of its load are known, but the dependence between component failures is unknown. With a physics-based approach, an optimization model is established so that narrow bounds of the system reliability can be generated. Three examples demonstrate that it is possible to produce narrower system reliability bounds than the traditional reliability bounds, thereby better assisting decision making during the early design stage.

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