Reliability analysis of non-repairable complex system with weighted subsystems connected in series

Negi, Seema; Singh, Sukhwinder

doi:10.1016/j.amc.2015.03.119

Cited by 31 publications

(13 citation statements)

References 6 publications

(4 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lisnianski and Levitin [8] used many real-world multi-state systems in which all the components had different performance levels and failure modes. Negi and Singh [9] studied the non-repairable complex system consisting of two subsystems, say, A and B, connected in series. They also evaluated the reliability, mean time to failure (MTTF), and sensitivity of the considered system with the use of UGF.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Network Reliability Characteristics and Importance of Components in a Communication Network

et al. 2021

View full text Add to dashboard Cite

Network reliability is one of the most important concepts in this modern era. Reliability characteristics, component significance measures, such as the Birnbaum importance measure, critical importance measure, the risk growth factor and average risk growth factor, and network reliability stability of the communication network system have been discussed in this paper to identify the critical components in the network, and also to quantify the impact of component failures. The study also proposes an efficient algorithm to compute the reliability indices of the network. The authors explore how the universal generating function can work to solve the problems related to the network using the exponentially distributed failure rate. To illustrate the proposed algorithm, a numerical example has been taken.

show abstract

Section: Introductionmentioning

confidence: 99%

Analysis of Network Reliability Characteristics and Importance of Components in a Communication Network

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Cekyay and Ozekici (2015) studied the coherent system in which the series connection of u-out-of-v standby subsystem with exponentially distributed component and evaluated the reliability characteristics. Negi and Singh (2015) computed reliability, MTTF, and sensitivity of a complex system having non-repairable weighted u-out-of-v: G connected in series with linear-(k, f, e): G and circular-(k, f, e): G configuration based on UGF. Wang et al (2016) analyzed the reliability optimization of a heterogeneous cold-standby system having uncertainty in parameter, compared interval numbers and provided an algorithm to evaluate the system reliability and expected mission cost using IUGF.…”

Section: Introductionmentioning

confidence: 99%

Reliability Evaluation of Repairable Parallel-Series Multi-State System Implementing Interval Valued Universal Generating Function

Renu

Bisht

Singh

2021

JRSS

View full text Add to dashboard Cite

In this paper, we have studied a repairable parallel-series multi-state system. The proposed system consists of m components in series and n components in parallel in which each component has three possible states. The interval universal generating function (IUGF) is presented, and the corresponding composition operators are defined. The reliability assessment of the considered system is done with the help of the IUGF approach. It is worth mentioning that IUGF got attention from various researchers due to its straightforwardness, less complexity, and universal applications. In the present model, probabilities of different components, reliability, sensitivity, and mean time to failure are evaluated with the help of the Markov process; Laplace-Steiltjes transform method applying IUGF. A numerical example has also been taken to illustrate the proposed technique.

show abstract

“…To analyze the reliability of the generalized linear multistate consecutively connected system, a UGFbased method was suggested [22]. Using UGF, the evaluation method of reliability characteristics for a nonrepair complex system has been presented [23].…”

Section: Introductionmentioning

confidence: 99%

Reliability and Sensitivity Analysis Method for a Multistate System with Common Cause Failure

Qin

Liu

2019

Complexity

View full text Add to dashboard Cite

With the increasing complexity of industrial products and systems, some intermediate states, other than the traditional two states, are often encountered during reliability assessments. A system with more than two states is called a multistate system (MSS) which has already become a general phenomenon in the components and/or systems. Moreover, common cause failure (CCF) often plays a very important role in the assessment of system reliability. A method is proposed to assess the reliability and sensitivity of an MSS with CCF. Some components are not only in a failure state that can cause failure itself, but also in a state that can cause the failure of other components with a certain probability. The components that are affected by one type of CCF make up some sets which can overlap on some components. Using the technology of a universal generating function (UGF), the CCF of a component can be incorporated in the expression of its UGF. Consequently, indices of reliability can be calculated based on the UGF expression of an MSS. Sensitivity analysis can help engineers to judge which type of CCF should be eliminated first under various resource limitations. Examples illustrate and validate this method.

show abstract

Reliability analysis of non-repairable complex system with weighted subsystems connected in series

Cited by 31 publications

References 6 publications

Analysis of Network Reliability Characteristics and Importance of Components in a Communication Network

Analysis of Network Reliability Characteristics and Importance of Components in a Communication Network

Reliability Evaluation of Repairable Parallel-Series Multi-State System Implementing Interval Valued Universal Generating Function

Reliability and Sensitivity Analysis Method for a Multistate System with Common Cause Failure

Contact Info

Product

Resources

About