A combined method for reliability analysis of multi-state system of minor-repairable components

Qin, Jinlei; Niu, Yuguang; Liu, Zheng

doi:10.17531/ein.2016.1.11

Cited by 14 publications

(12 citation statements)

References 43 publications

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“…Testing multistate systems was introduced in [14][15][16][17][18][19][25][26]. The article [7] uses fuzzy variables (fuzzy sets), while paper [22] examines multistate systems with components requiring minimal repair. Using simulation methods for testing preventive renewals was presented in paper [20].…”

Section: Introductionmentioning

confidence: 99%

Multi-state model of maintenance policy

Knopik¹,

Migawa²

2018

Eksploatacja i Niezawodność – Maintenance and Reliability

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Preventive replacement is applied to improve the device availability or increase the profit per unit time of the maintenance system. In this paper, we study age-replacement model of technical object for n-state system model. The criteria function applied in this paper describe profit per unit time or coefficient of availability. The probability distribution of a unit‘s failure time is assumed to be known, and preventive replacement strategy will be used over very long period of time. We investigate the problem of maximization of profit per unit time and coefficient availability for increasing the failure rate function of the lifetime and for a wider class of lifetime. The purpose of this paper is to obtain conditions under which the profit per unit time approaches a maximum. In this paper we shows that the criteria function (profit per unit time or coefficient availability) can be expressed using the matrix calculation method. Finally, a numerical example to evaluate an optimal replacement age is presented.

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Section: Introductionmentioning

confidence: 99%

Multi-state model of maintenance policy

Knopik¹,

Migawa²

2018

Eksploatacja i Niezawodność – Maintenance and Reliability

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“…Suppose that W is a discrete random variable to denote certain performance level of MSS and can adopt values from L. Combining (1) and the above modeling of components and MSS, the system function of the MSS can be written as 2 Complexity…”

Section: Modeling Of Mssmentioning

confidence: 99%

“…e analysis of MSS entails the development of new representation, modeling, and quantification technologies. A few researchers had focused on the above-mentioned aspects [2][3][4][5]. A new approach based on logical differential calculus is proposed for importance analysis and application of MSS, where MSS states change depending on simultaneous changing of some components' states [6,7].…”

Section: Introductionmentioning

confidence: 99%

Protection Mechanism in Reliability Evaluation Approach to Multistate System with Common Cause Failure

2021

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Except the two types of state, complete failure and perfect functioning, some intermediate states also existed between those two states. This characteristic enables multistate system (MSS) whose components are often of more than two states. Moreover, because of dependence between components, common cause failure (CCF) enhances the failure risk of components during the operating period of MSS. A protection mechanism needs to be adopted because of the importance of certain components. For a MSS with CCF and protection mechanism, its reliability can be evaluated by a proposed approach. Certain components not only can cause failure at one state, but also can cause failure to other components because of the CCF. Under the impact of one type of CCF, those components can constitute a specific group that can overlap with certain components. Universal generating function (UGF) is adopted to incorporate the CCF and protection mechanism of a component. Consequently, reliability indices of a MSS can be evaluated by the proposed approach based on UGF. Examples and comparisons illustrate and validate this method. This method can also help engineers prioritize elements that require protection mechanism under various resource limitations.

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“…Due to the advantages of convenient computation and easy analysis, UGF has been widely studied in reliability evaluation and optimization of MSSs. It has gradually become one of the most basic and commonly used methods for the reliability assessment of MSSs [2,[14][15].…”

Section: Introductionmentioning

confidence: 99%

Reliability Evaluation of Uncertain Multi-State Systems based on Weighted Universal Generating Function

Dong¹

2019

IJPE

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Universal generating function (UGF) is a basic and important technology in the reliability evaluation of multi-state systems (MSSs). It has been widely noticed by reliability scholars and engineers since its introduction. In the process of reliability evaluation of MSSs with UGF, universal generating operators play a great role in synthesizing the system output performance rate. For many uncertain MSSs in actual engineering, when the connection structure between components is unknown and/or the performance relationship is unclear, the definition of the weighted universal generating function is proposed. By designing reliability evaluation indices and constructing a weighted universal generating function of MSSs, reliability parameters of MSSs can be evaluated. A real case of steam turbine power generation system in a repairable naval equipment system is conducted to illustrate the applications.

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A combined method for reliability analysis of multi-state system of minor-repairable components

Abstract: Article citation info: Qin J, niu Y, Li Z. A combined method for reliability analysis of multi-state system of minor-repairable components. Eksploatacja i niezawodnosc - Maintenance and Reliability 2016; 18 (1): 80-88, http://dx.doi.org/10.17531/ein.2016

Cited by 14 publications

References 43 publications

Multi-state model of maintenance policy

Multi-state model of maintenance policy

Protection Mechanism in Reliability Evaluation Approach to Multistate System with Common Cause Failure

Reliability Evaluation of Uncertain Multi-State Systems based on Weighted Universal Generating Function

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