Simulation approach to estimate the system reliability of a time-based capacitated flow network susceptible to correlated failures

2013 ◽  
Vol 36 ◽  
pp. 74-83 ◽  
Author(s):  
Yi-Kuei Lin ◽  
Lance Fiondella ◽  
Ping-Chen Chang
Keyword(s):  
System Reliability ◽  
Simulation Approach ◽  
Flow Network ◽  
Correlated Failures

Modeling multi-state system reliability analysis in a power station under fatal and nonfatal shocks: a simulation approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Reza Pourhassan ◽  
Sadigh Raissi ◽  
Arash Apornak
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
System Performance ◽  
Failure Process ◽  
State System ◽  
Failure Behavior ◽  
Simulation Approach ◽  
Critical System ◽  
Content Type ◽  
System Reliability Analysis

PurposeIn some environments, the failure rate of a system depends not only on time but also on the system condition, such as vibrational level, efficiency and the number of random shocks, each of which causes failure. In this situation, systems can keep working, though they fail gradually. So, the purpose of this paper is modeling multi-state system reliability analysis in capacitor bank under fatal and nonfatal shocks by a simulation approach.Design/methodology/approachIn some situations, there may be several levels of failure where the system performance diminishes gradually. However, if the level of failure is beyond a certain threshold, the system may stop working. Transition from one faulty stage to the next can lead the system to more rapid degradation. Thus, in failure analysis, the authors need to consider the transition rate from these stages in order to model the failure process.FindingsThis study aims to perform multi-state system reliability analysis in energy storage facilities of SAIPA Corporation. This is performed to extract a predictive model for failure behavior as well as to analyze the effect of shocks on deterioration. The results indicate that the reliability of the system improved by 6%.Originality/valueThe results of this study can provide more confidence for critical system designers who are engaged on the proper system performance beyond economic design.

Optimal Reliability and Cost of Non-Repairable Systems Subject to Two Failure Modes Considering Correlated Failures

2018 ◽  
Vol 25 (05) ◽  
pp. 1850024
Author(s):  
Anusha Krishna Murthy ◽  
Saikath Bhattacharya ◽  
Lance Fiondella
Keyword(s):  
Failure Mode ◽  
System Reliability ◽  
Failure Modes ◽  
Optimal Number ◽  
Optimal Designs ◽  
Repairable Systems ◽  
Independent Manner ◽  
Reliability Models ◽  
Correlated Failures ◽  
The Impact

Most reliability models assume that components and systems experience one failure mode. Several systems such as hardware, however, are prone to more than one mode of failure. Past two-failure mode research derives equations to maximize reliability or minimize cost by identifying the optimal number of components. However, many if not all of these equations are derived from models that make the simplifying assumption that components fail in a statistically independent manner. In this paper, models to assess the impact of correlation on two-failure mode system reliability and cost are developed and corresponding expressions for reliability and cost optimal designs derived. Our illustrations demonstrate that, despite correlation, the approach identifies reliability and cost optimal designs.

A New Algorithm to Generate d-Minimal Paths in a Multistate Flow Network with Noninteger ARC Capacities

1998 ◽  
Vol 05 (03) ◽  
pp. 269-285 ◽  
Author(s):  
Yi-Kuei Lin ◽  
John Yuan
Keyword(s):  
System Reliability ◽  
Time Complexity ◽  
Lower Boundary ◽  
Computational Time ◽  
Sink Node ◽  
Real Numbers ◽  
Worst Case ◽  
Flow Network ◽  
Minimal Paths ◽  
System Flow

This article is mainly to study the reliability evaluation in terms of MPs (minimal paths) for a multistate flow network G in which the capacities of each arc are real numbers. The transportation system from the source node s to the sink node t is one of such typical networks. Given the system demand d from s to t and MPs in advance, an algorithm is proposed first to find out all lower boundary points of level d (namely d-MPs here). The system reliability which is the probability that the system flow satisfies the demand d can be calculated in terms of such d-MPs. One example is presented to illustrate how all its d-MPs are generated. The computational time complexity in the worst case and average cases for such an algorithm is presented.

Discrete and Continuous Consecutive 2-Out-of-n:F System Reliability with Correlated Components

2017 ◽  
Vol 24 (04) ◽  
pp. 1750016 ◽  
Author(s):  
Bentolhoda Jafary ◽  
Lance Fiondella ◽  
Liudong Xing
Keyword(s):  
System Reliability ◽  
Residual Life ◽  
Critical Infrastructures ◽  
Mean Residual Life ◽  
Continuous Systems ◽  
Time To Failure ◽  
Correlated Failures ◽  
Component Failures ◽  
Correlated Components ◽  
F System

A linear consecutive [Formula: see text]-out-of-[Formula: see text]:failed system, henceforth written consecutive [Formula: see text]-out-of-[Formula: see text]:F, is an [Formula: see text]-component system that fails if [Formula: see text] or more consecutive components in positions [Formula: see text] fail, where [Formula: see text]. The consecutive [Formula: see text]-out-of-[Formula: see text]:F system model is particularly valuable for characterizing critical infrastructures such as telecommunications that provide essential services to society. However, events that impact critical infrastructures such as natural disasters often produce geospatially correlated failures, necessitating reliability models that can accommodate these scenarios where component failures may be correlated. This paper presents a method to explicitly model the correlation between component failures of a consecutive [Formula: see text]-out-of-[Formula: see text]:F system. The approach produces analytical expressions for the reliability of discrete and continuous systems in terms of component reliabilities and correlation between the component failures. The explicit correlation parameter simplifies sensitivity analysis for a variety of measures of interest, including reliability, density function, hazard rate, mean time to failure (MTTF), availability, and mean residual life (MRL). It is illustrated through examples where correlated failures can negatively influence system reliability. Thus, the approach can quantify improvements to system reliability that could be achieved by lowering the correlation between failures of system components.

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