Computation Interval-Valued Reliability of Sliding Window System

In this study, a sliding window system is revisited and evaluated interval-valued reliability in case of upper and lower form with the help of universal generating function technique and using an algorithm, how to compute the reliability of sliding window system. Computation of probability by interval-valued is most uses but universal generating function method given improved results within it. An example is also taken at the end to demonstrate the system.

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Signature of A-Within-B-From-D/G Sliding Window System

International Journal of Mathematical Engineering and Management Sciences ◽

10.33889/ijmems.2019.4.1-009 ◽

2019 ◽

Vol 4 (1) ◽

pp. 95-107 ◽

Cited By ~ 2

Author(s):

Akshay Kumar ◽

S. B. Singh

Keyword(s):

Generating Function ◽

Sliding Window ◽

Expected Value ◽

Coherent System ◽

Multiple Failures ◽

System Sensitivity ◽

Window System ◽

Universal Generating Function

In this study, we have proposed a model of the sliding window coherent system in case of multiple failures. The considered model consists of G linearly required multi-state elements and G number of parallel elements in A-within-B-from-D/G for each multi-state. The system fails if at least A group elements out of B consecutive of D consecutive multi-state elements have performance lower than the weight w. We have evaluated the signature reliability, expected value and system sensitivity on the basis of the extended universal generating function of the considered system.

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Optimal allocation of multi-state elements in a sliding window system with phased missions

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability ◽

10.1177/1748006x20946165 ◽

2020 ◽

pp. 1748006X2094616

Author(s):

Kunxiang Yi ◽

Gang Kou ◽

Kaiye Gao ◽

Hui Xiao

Keyword(s):

Intelligent Transportation Systems ◽

High Performance ◽

Optimal Allocation ◽

Sliding Window ◽

Heating System ◽

Degradation Process ◽

Transportation Systems ◽

Function Technique ◽

Window System ◽

Evaluation Algorithm

Many real-world engineering systems such as aerospace systems, intelligent transportation systems and high-performance computing systems are designed to complete missions in multiple phases. These types of systems are known as phased-mission systems. Inspired by an industrial heating system, this research proposes a generalized linear sliding window system with phased missions. The proposed system consists of N nodes with M multi-state elements that are subject to degradation. The linear sliding window system fails if the cumulative performance of any r consecutive nodes is less than the pre-determined demand in any phase. The degradation process of each element is modeled by a continuous-time Markov chain. A novel reliability evaluation algorithm is proposed for the linear sliding window system with phased missions by extending the universal generating function technique. Furthermore, the optimal element allocation strategy is determined using the particle swarm optimization. The effectiveness of the proposed algorithm is confirmed by a set of numerical experiments.

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A Novel Label Universal Generating Function Method for Evaluating the One-to-all-Subsets General Multistate Information Network Reliability

IEEE Transactions on Reliability ◽

10.1109/tr.2011.2134310 ◽

2011 ◽

Vol 60 (2) ◽

pp. 470-478 ◽

Cited By ~ 9

Author(s):

Wei-Chang Yeh ◽

Yuan-Ming Yeh

Keyword(s):

Generating Function ◽

Function Method ◽

Network Reliability ◽

Information Network ◽

The One ◽

Universal Generating Function

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Discrete Interval-Valued Stress-Strength Interference Model Based on the Extended Universal Generating Function

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.246-247.441 ◽

2012 ◽

Vol 246-247 ◽

pp. 441-445 ◽

Cited By ~ 1

Author(s):

Hui Xin Guo ◽

Xiao Bin Pang ◽

Xin Fa Yang ◽

Li Zhi Cheng

Keyword(s):

Experimental Data ◽

Generating Function ◽

Random Variable ◽

Reliability Estimation ◽

Interference Model ◽

Upper And Lower Bounds ◽

Machine Component ◽

Discrete Interval ◽

Interval Valued ◽

Universal Generating Function

A new approach was proposed to estimate the reliability of a machine component when the probability density functions of stress and strength can not be exactly determined or only finite experiment data of stress and strength are available. The conventional universal generating function was introduced and then it was extended to represent the discrete interval-valued random variable. The experimental data of stress and strength were formulated as two discrete interval-valued random variables. Based on the extended universal generating function, a discrete interval-valued stress-strength interference model was proposed. An approach was proposed to solve the proposed stress-strength interference model and it can be used to calculate the upper and lower bounds of the component reliability. An example was given to demonstrate the proposed approach. It is showed that the proposed approach is suitable to the reliability estimation of a machine component when only finite experimental data of stress and strength can be obtained.

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