Automotive electromagnetic engineering: system reliability issues and challenges

2007 ◽  
Author(s):  
A. Ruddle
Keyword(s):  
System Reliability ◽  
Engineering System

THE JOINT PREDICTIVE-POSTERIOR METHOD IN THE BAYESIAN ANALYSIS OF STRESS-STRENGTH RELIABILITY

2007 ◽  
Vol 14 (01) ◽  
pp. 29-47 ◽  
Author(s):  
T. PHAM-GIA ◽  
N. TURKKAN
Keyword(s):  
Quality Control ◽  
Bayesian Analysis ◽  
Control Problem ◽  
System Reliability ◽  
Posterior Approach ◽  
Highway Bridge ◽  
Engineering System ◽  
Strength Model ◽  
Combined Approach ◽  
Engineering Applications

The joint predictive-posterior approach to the study of the reliability of an engineering system, under a stress-strength model, is presented in this article. This new combined approach is original, is supported by charts and graphs and can be quite useful since it allows the realistic forecasting of system reliability, with known credibility levels, ahead of real experimentation and testing results. In this article, it is concretely illustrated by several engineering applications related to a highway bridge study and a quality control problem.

scholarly journals Failure Mode and Effect Analysis a Tool for Reliability Evaluation: Review

2018 ◽  
Vol 3 (4) ◽  
pp. 65 ◽  
Author(s):  
Adeniran Sunday Afolalu ◽  
Y. Salawu Enesi ◽  
Oluyemi Kehinde ◽  
U. Ayuba Samuel ◽  
V. Ihebom Ikechi ◽  
...  
Keyword(s):  
Failure Mode ◽  
System Reliability ◽  
Failure Modes ◽  
High Reliability ◽  
Engineering System ◽  
Medical Field ◽  
Effect Analysis ◽  
Engineering Equipment ◽  
Turbine Component ◽  
Component Manufacturing

The purpose of safety designing is generally not on cost, but rather on saving life and nature, and consequently bargains just with specific risky system failure modes. High reliability levels are the consequence of good designing, scrupulousness and dependably never the aftereffect of re-dynamic failure management. Failure mode and effect analysis (FMEA) is a helpful technique analyzing engineering system reliability. The study focused on the use of FMEA technique to analyze the reliability of engineering equipment or components in selected areas such as: Wind Turbine component, Manufacturing Industries, Medical field and in evaluating the performances of Robots in different fields. The study showed the importance of FMEA as used widely in analyzing engineering equipment with regards to reliability.

scholarly journals Engineering System Reliability State Identification Methodology

2008 ◽  
Vol 8 (1) ◽  
Author(s):  
Jerzy Jaźwiński ◽  
Janusz Szpytko ◽  
Józef Żurek
Keyword(s):  
System Reliability ◽  
Engineering System ◽  
State Identification

One-class support vector machines with a bias constraint and its application in system reliability prediction

2019 ◽  
Vol 33 (03) ◽  
pp. 346-358 ◽  
Author(s):  
Zhengwei Hu ◽  
Zhangli Hu ◽  
Xiaoping Du
Keyword(s):  
System Reliability ◽  
Failure Modes ◽  
Joint Probability ◽  
Probability Of Failure ◽  
Design Stage ◽  
Support Vector ◽  
Engineering System ◽  
Failure Data ◽  
Design Variables ◽  
The One

AbstractSupport vector machine (SVM) methods are widely used for classification and regression analysis. In many engineering applications, only one class of data is available, and then one-class SVM methods are employed. In reliability applications, the one-class data may be failure data since the data are recorded during reliability experiments when only failures occur. Different from the problems handled by existing one-class SVM methods, there is a bias constraint in the SVM model in this work and the constraint comes from the probability of failure estimated from the failure data. In this study, a new one-class SVM regression method is proposed to accommodate the bias constraint. The one class of failure data is maximally separated from a hypersphere whose radius is determined by the known probability of failure. The proposed SVM method generates regression models that directly link the states of failure modes with design variables, and this makes it possible to obtain the joint probability density of all the component states of an engineering system, resulting in a more accurate prediction of system reliability during the design stage. Three examples are given to demonstrate the effectiveness of the new one-class SVM method.

The effects of relative system reliability and prioritization on alarm reaction patterns

2006 ◽  
Author(s):  
Elizabeth T. Newlin ◽  
Ernesto A. Bustamante ◽  
James P. Bliss ◽  
Randall D. Spain ◽  
Corey K. Fallon
Keyword(s):  
System Reliability ◽  
Alarm Reaction ◽  
Reaction Patterns
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