Reliability Analysis of k-out-of-n: G System: A Short Review

Krishnan, Ragi

doi:10.31873/ijeas.7.02.12

Cited by 1 publication

(1 citation statement)

References 27 publications

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“…Some reviews of the literature also present interesting perspectives on reliability. The authors of [45] propose a summary of the literature on the application of the k-out-of-n: G system method for evaluating the reliability of the system. This method aims to analyze the reliability of a system consisting of n components, which can operate as long as k components function.…”

Section: Related Workmentioning

confidence: 99%

Machine Learning Applications for Reliability Engineering: A Review

Payette

Abdul-Nour

2023

Sustainability

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The treatment of big data as well as the rapid improvement in the speed of data processing are facilitated by the parallelization of computations, cloud computing as well as the increasing number of artificial intelligence techniques. These developments lead to the multiplication of applications and modeling techniques. Reliability engineering includes several research areas such as reliability, availability, maintainability, and safety (RAMS); prognostics and health management (PHM); and asset management (AM), aiming at the realization of the life cycle value. The expansion of artificial intelligence (AI) modeling techniques combined with the various research topics increases the difficulty of practitioners in identifying the appropriate methodologies and techniques applicable. The objective of this publication is to provide an overview of the different machine learning (ML) techniques from the perspective of traditional modeling techniques. Furthermore, it presents a methodology for data science application and how machine learning can be applied in each step. Then, it will demonstrate how ML techniques can be complementary to traditional approaches, and cases from the literature will be presented.

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Section: Related Workmentioning

confidence: 99%