Redundancy optimization problems for systems with dependent failure rates

1991 ◽  
Vol 31 (6) ◽  
pp. 1097-1099 ◽  
Author(s):  
A. Bhattacharya ◽  
A.K. Bhattacharji
Keyword(s):  
Optimization Problems ◽  
Failure Rates ◽  
Dependent Failure ◽  
Redundancy Optimization

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.

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

2013 ◽  
Vol 4 (1) ◽  
pp. 25-39 ◽  
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.

Redundancy optimization for multi-state series-parallel systems using ordinal optimization-based-genetic algorithm

2021 ◽  
pp. 1748006X2110286
Author(s):  
Yishuang Hu ◽  
Yi Ding ◽  
Zhiguo Zeng
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Optimization Problems ◽  
Real Life ◽  
Parallel Systems ◽  
Function Technique ◽  
Ordinal Optimization ◽  
Engineering Systems ◽  
Designing Method ◽  
Redundancy Optimization

Multi-state series-parallel systems (MSSPSs) are widely-used for representing engineering systems. In real-life cases, engineers need to design an optimal MSSPS structure by combining different versions and number of redundant components. The objective of the design is to ensure reliability requirements using the least costs, which could be formulated as a redundancy optimization problem under reliability constraints. The genetic algorithm is one of the most frequently used method for solving redundancy optimization problems. In traditional genetic algorithms, the population size needs to be determined based on the experience of the modeler. Often, this ends up creating a large number of unnecessary samples. As a result, the computational burden can be huge, especially for large-scale MSSPS structures. To solve these problems, this paper proposes an optimal structure designing method named as redundancy ordinal optimization. The universal generating function technique is applied to evaluate the reliabilities of the MSSPSs. Based on the reliabilities, an ordinal optimization algorithm is adapted to update the parent populations and the stopping criterion of genetic algorithm, so that the unnecessary structure designs can be eliminated. Numerical examples show that the proposed method improves the computational efficiency while remaining satisfactorily accurate.

scholarly journals Methodology for Determining Time-Dependent Lead Battery Failure Rates from Field Data

Batteries ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. 39
Author(s):  
Rafael Conradt ◽  
Frederic Heidinger ◽  
Kai Peter Birke
Keyword(s):  
Power Supply ◽  
Failure Modes ◽  
Time Dependent ◽  
Failure Rates ◽  
Reliability Models ◽  
Safety Critical ◽  
Lead Battery ◽  
Reliable Power Supply ◽  
The Individual ◽  
Dependent Failure

The safety requirements in vehicles continuously increase due to more automated functions using electronic components. Besides the reliability of the components themselves, a reliable power supply is crucial for a safe overall system. Different architectures for a safe power supply consider the lead battery as a backup solution for safety-critical applications. Various ageing mechanisms influence the performance of the battery and have an impact on its reliability. In order to qualify the battery with its specific failure modes for use in safety-critical applications, it is necessary to prove this reliability by failure rates. Previous investigations determine the fixed failure rates of lead batteries using data from teardown analyses to identify the battery failure modes but did not include the lifetime of these batteries examined. Alternatively, lifetime values of battery replacements in workshops without knowing the reason for failure were used to determine the overall time-dependent failure rate. This study presents a method for determining reliability models of lead batteries by investigating individual failure modes. Since batteries are subject to ageing, the analysis of lifetime values of different failure modes results in time-dependent failure rates of different magnitudes. The failure rates of the individual failure modes develop with different shapes over time, which allows their ageing behaviour to be evaluated.

Sign in / Sign up

Export Citation Format

Share Document