An intelligent predictive maintenance system based on random forest for addressing industrial conveyor belt challenges

An intelligent predictive maintenance system based on random forest for addressing industrial conveyor belt challenges

This study introduces a sophisticated intelligent predictive maintenance system for industrial conveyor belts powered by a random forest machine learning model. The random forest model was evaluated against established models such as logistic regression, neural networks, decision trees, and gradient...

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Bibliographic Details
Main Authors: Mingyu Wu, Kai Woon Goh, Kam Heng Chaw, Ye Sheng Koh, Marvin Dares, Che Fai Yeong, Eileen L. M. Su, Holderbaum William, Yunhui Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Mechanical Engineering
Subjects:
predictive maintenance
conveyor belt systems
random forest
machine learning
operational efficiency
comparative analysis
Online Access:https://www.frontiersin.org/articles/10.3389/fmech.2024.1383202/full
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https://www.frontiersin.org/articles/10.3389/fmech.2024.1383202/full

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