Industrial System Performance Under Multistate Failures with Standby Mode

Kumar, Amit; Ram, Mangey; Pant, Sangeeta; Kumar, Anuj

doi:10.1007/978-3-319-60432-9_4

Cited by 10 publications

(5 citation statements)

References 23 publications

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“…The main goal of the MCDM technique [12] is to choose the weights for each criterion. The decision-making process in AHP begins, as its name implies, with the breakdown of the MCDM problem [13,14], into a hierarchy mode.…”

Section: Analytic Hierarchy Process and Pair-wise Comparison Matrixmentioning

confidence: 99%

A Review Based on Various Applications to Find a Consistent Pairwise Comparison Matrix

Kaushik,

Pant,

Joshi

et al. 2024

JRSS

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Multi-criteria decision-making (MCDM) is a crucial process that provides a systematic approach to resolving numerous challenging problems encountered in everyday life. An effective method for addressing such MCDM challenges is the Analytic Hierarchy Process (AHP). Within AHP, the resolution of these problems relies on the Pairwise Comparison Matrix (PCM), a pivotal component of the decision-making framework. A fundamental aspect of AHP lies in ensuring the consistency of the comparison matrix to validate the logical perspective of the respondents. An inconsistent matrix undermines its utility as a reference for decision-making, underscoring the significance of achieving consistency in the PCM as a pivotal stage in the decision-making process. In this discourse, we delve into various methodologies aimed at deriving a refined and consistent PCM capable of replacing the original inconsistent version. To facilitate comprehension, we categorize the references based on proposed approaches and specific focal points.

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Section: Analytic Hierarchy Process and Pair-wise Comparison Matrixmentioning

confidence: 99%

A Review Based on Various Applications to Find a Consistent Pairwise Comparison Matrix

Kaushik,

Pant,

Joshi

et al. 2024

JRSS

View full text Add to dashboard Cite

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“…Here, the author proposes, in the context of Markov process modelling and stationary performance measure, an importance measure based on partial derivative with respect to a parameter. This measure, also called multi-directional sensitivity measure, can be an efficient tool to investigate not only the importance of a given component, but also the importance of a class of components, the importance of a system state and, more generally, the effect of the simultaneous change of several design parameters that are related to the components or the system’s state (Do Van et al , 2008; Peng et al , 2012; Zaitseva, 2012; Kumar et al , 2018; Kumar et al , 2017). In the present paper, this analysis has been done for system reliability as well as MTTF for finding which failure affects the system reliability and MTTF the most.…”

Section: Numerical Analysis and Assessment Of Various Reliability Measuresmentioning

confidence: 99%

Sensitivity and reliability evaluation for a thermal power plant subject to complex failures and human error

Kumar

2019

MMMS

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Purpose The purpose of this paper is to analyze a thermal power plant (TPP) by taking into consideration its key components, namely, boiler, turbine, conveyor and generator, which are handled by a human operator. It is well known fact that the continuous power generation through a power plant depends on the reliability/availability of its components. Design/methodology/approach The various performance measures of a TPP are obtained by using mathematical modeling, Markov process and supplementary variable technique. Findings Reliability, i.e. mean time to failure with respect to different components of a TPP, has been obtained and demonstrated with the help of graphs. Critical components of the system are identified through sensitivity analysis. Originality/value In the present paper, a mathematical model based on the functioning of a TPP has been developed. Conclusions in this paper are good references for the design of a TPP.

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“…Reliability can be viewed as the probability that a system works uninterrupted for a specific period of time. Reliability is also defined as the probability that a product, system, or service will perform its intended function adequately for a specified period of time, or at least operate in a defined environment without failure [2][3][4]. This definition encourages system engineers to develop a reliable and cost-effective product, which, in turn, increases the complexities and creates a complex system design process and, hence, a complex SROP.…”

Section: Introductionmentioning

confidence: 99%

Modified Wild Horse Optimizer for Constrained System Reliability Optimization

Kumar

Pant²,

Singh

et al. 2023

Axioms

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The last few decades have witnessed advancements in intelligent metaheuristic approaches and system reliability optimization. The huge progress in metaheuristic approaches can be viewed as the main motivator behind further refinement in the system reliability optimization process. Researchers have intensively studied system reliability optimization problems (SROPs) to obtain the optimal system design with several constraints in order to optimize the overall system reliability. This article proposes a modified wild horse optimizer (MWHO) for SROPs and investigates the reliability allocation of two complex SROPs, namely, complex bridge system (CBS) and life support system in space capsule (LSSSC), with the help of the same process. The effectiveness of this framework based on MWHO is demonstrated by comparing the results obtained with the results available in the literature. The proposed MWHO algorithm shows better efficiency, as it provides superior solutions to SROPs.

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Industrial System Performance Under Multistate Failures with Standby Mode

Cited by 10 publications

References 23 publications

A Review Based on Various Applications to Find a Consistent Pairwise Comparison Matrix

A Review Based on Various Applications to Find a Consistent Pairwise Comparison Matrix

Sensitivity and reliability evaluation for a thermal power plant subject to complex failures and human error

Modified Wild Horse Optimizer for Constrained System Reliability Optimization

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