Leveraging feature extraction and risk-based clustering for advanced fault diagnosis in equipment.

Leveraging feature extraction and risk-based clustering for advanced fault diagnosis in equipment.

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In the contemporary manufacturing landscape, the advent of artificial intelligence and big data analytics has been a game-changer in enhancing product quality. Despite these advancements, their application in diagnosing failure probability and risk remains underexplored. The current practice of fail...

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Bibliographic Details
Main Authors: Hyeonbin Ji, Ingeun Hwang, Junghwon Kim, Suan Lee, Wookey Lee
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0314931
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