Signature-based approach for stress-strength systems

Pakdaman, Zohreh; Ahmadi, Jafar; Doostparast, Mahdi

doi:10.1007/s00362-017-0889-5

Cited by 12 publications

(2 citation statements)

References 14 publications

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“…Gürler 31 considered the MRS for the systems that consist of 𝑛 independent components under some structures when the stress and the strength are independent random variables. For some recent studies on MRS, see Bayramoglu et al, 32 Pakdaman et al 33 and Kizilaslan. 34 The MRS of a component under the stress 𝑌, denoted by 𝜙 𝑌 , is the expected value of the remaining strength as given below (see, Gürler 31 )…”

Section: Mrs For We Distribution In a Stress-strength Setupmentioning

confidence: 99%

Fuzzy stress‐strength reliability for weighted exponential distribution

Yazgan

Gürler

Esemen

et al. 2021

Quality & Reliability Eng

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This study considers the reliability of the stress-strength model in the presence of the fuzziness when the stress and strength variables have weighted exponential distribution with the common shape parameter. It obtains the mean remaining strength and fuzzy mean remaining strength for the weighted exponential distribution in order to calculate how long a component can live on average under the stress. The comparative simulation results with conventional and fuzzy approaches are presented to observe the effect of the parameter changes on the models using the maximum likelihood method for different sample sizes. In addition, the developed models are applied to two real data and estimation results were generated for two approaches.

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Section: Mrs For We Distribution In a Stress-strength Setupmentioning

confidence: 99%

Fuzzy stress‐strength reliability for weighted exponential distribution

Yazgan

Gürler

Esemen

et al. 2021

Quality & Reliability Eng

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“…The author described the methods in terms of univariate contingent probability mass functions with the target of outlining some related properties of the concepts of signature, relative quality functions and reliability functions. Pakdaman et al (2019) used signatures to determine the stress-strength system reliability. The functioning of the stressstrength reliability had been evaluated with the help of signature-based properties of strength devices.…”

Section: Introductionmentioning

confidence: 99%

UGF-based signature reliability for solar panel k-out-of-n- multiplex systems

Ram

Kumar

Naaz

2023

JQME

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PurposeThe purpose of this paper is to evaluate the reliability and signature reliability of solar panel k-out-of-n-multiplex system with the help of universal generating function.Design/methodology/approachEnergy scarcity and global warming issues have become important concerns for humanity in recent decades. To solve these problems, various nations work for renewable energy sources (RESs), including sun, breeze, geothermal, wave, radioactive and biofuels. Solar energy is absorbed by solar panels, referred to as photovoltaic panels, which then transform it into electricity that can be used to power buildings or residences. Remote places can be supplied with electricity using these panels. Solar energy is often generated using a solar panel that is connected to an inverter for power supply. As a result, a converter reliability evaluation is frequently required. This paper presents a study on the reliability analysis of k-out-of-n systems with heterogeneous components. In this research, the universal generating function methodology is used to identify the reliability function and signature reliability of the solar array components. This method is commonly used to assess the tail signature and Barlow-Proschan index with independent and identically distributed components.FindingsThe Barlow-Proschan index, tail signature, signature, expected lifetime, expected cost and minimal signature of independent identically distributed are all computed.Originality/valueThis is the first study of solar panel k-out-of-n-multiplex systems to examine the signature reliability with the help of universal generating function techniques with various measures.

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