Survey of Reliability Analysis of Weighted K-out-of-N System

Computer controlled systems used in critical care systems often utilize redundancy to achieve the required level of reliability. However, as highly designed systems become more functionally integrated, they generally consist of several kinds of components with unique purposes. This kind of fault-tolerant system design is especially crucial for vital applications including energy systems, medical devices, and aircraft. With extensive applications in engineering systems both in industry and military, a considerable amount of research has been carried out in the area of redundant systems. The most prevalent kind of redundancy is k-out-of-n type redundancy. In order to develop high reliability systems, redundant models like k out of n systems have been developed. In normal circumstances, each component's contribution to system reliability will differ. When a system has weighted components, each component makes a unique contribution to the system's overall performance. Performance of the system is influenced by both system operation and the sum of the components that make up it. This survey paper provides a general overview of the different types of weighted- k-out-of-n: G systems, methods adapted to their reliability assessment, lifetime distributions and stochastic order of these systems. In order to analyse the various models of weighted k-out-of-n systems, an in-depth investigation is conducted.

Authors

Institutions

Publication Details

Journal
Science Journal of Applied Mathematics and Statistics
Published
2025-02-10
DOI
https://doi.org/10.11648/j.sjams.20251301.12
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Survey of Reliability Analysis of Weighted K-out-of-N System

R. Sanjay Krishnan
1 links
Science Journal of Applied Mathematics and Statistics
Probabilistic and Robust Engineering Design
article

Survey of Reliability Analysis of Weighted K-out-of-N System

R. Sanjay Krishnan
article en

Abstract

Computer controlled systems used in critical care systems often utilize redundancy to achieve the required level of reliability. However, as highly designed systems become more functionally integrated, they generally consist of several kinds of components with unique purposes. This kind of fault-tolerant system design is especially crucial for vital applications including energy systems, medical devices, and aircraft. With extensive applications in engineering systems both in industry and military, a considerable amount of research has been carried out in the area of redundant systems. The most prevalent kind of redundancy is k-out-of-n type redundancy. In order to develop high reliability systems, redundant models like k out of n systems have been developed. In normal circumstances, each component's contribution to system reliability will differ. When a system has weighted components, each component makes a unique contribution to the system's overall performance. Performance of the system is influenced by both system operation and the sum of the components that make up it. This survey paper provides a general overview of the different types of weighted- k-out-of-n: G systems, methods adapted to their reliability assessment, lifetime distributions and stochastic order of these systems. In order to analyse the various models of weighted k-out-of-n systems, an in-depth investigation is conducted.

Science Journal of Applied Mathematics and StatisticsVol. 13(1)
PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN)
Openalex Percentile: Top 96%
Probabilistic and Robust Engineering Design
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.