Machine learning approaches for equipment failure prediction and predictive maintenance: a comprehensive review; Молодежь и современные информационные технологии

Machine learning approaches for equipment failure prediction and predictive maintenance: a comprehensive review; Молодежь и современные информационные технологии

Bibliographic Details
Parent link:Молодежь и современные информационные технологии.— 2024.— С. 123-125
Main Author: Ayitha Krishna Likhit
Summary:This comprehensive review explores the application of machine learning techniques in predicting equipment failures and facilitating predictive maintenance strategies. Drawing from recent literature and case studies, the paper examines various machine learning algorithms and methodologies employed in this domain. Key findings highlight the effectiveness of machine learning models in pre emptively identifying potential equipment failures, thereby enhancing maintenance practices and minimizing downtime. Implications for industries reliant on machinery and suggestions for future research directions are discussed
Текстовый файл
Language:English
Published: 2024
Series:Искусственный интеллект, машинное обучение и большие данные
Subjects:
электронный ресурс
труды учёных ТПУ
machine learning
predictive maintenance
equipment failure prediction
Online Access:http://earchive.tpu.ru/handle/11683/84806
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=675331

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