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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31322
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dc.contributor.authorSicard B-
dc.contributor.authorAlsadi N-
dc.contributor.authorSpachos P-
dc.contributor.authorZiada Y-
dc.contributor.authorGadsden SA-
dc.contributor.editorChakrabarti S-
dc.contributor.editorPaul R-
dc.contributor.editorGill B-
dc.contributor.editorGangopadhyay M-
dc.contributor.editorPoddar S-
dc.date.accessioned2025-03-03T20:42:15Z-
dc.date.available2025-03-03T20:42:15Z-
dc.date.issued2022-06-04-
dc.identifier.urihttp://hdl.handle.net/11375/31322-
dc.description.abstractTo maximize efficiency, quality of products, and profits, it is important to maintain machine tools to reduce downtime and maximize output. Predictive maintenance is the most efficient method of condition monitoring and maintenance. An Internet of Things approach can help implement an autonomous predictive CM system in manufacturing facilities. The critical parameters of sensor selection, communication, and data analysis have been examined. The components that make up an effective IoT CM system have been discussed and analyzed. An IoT approach has been shown to eliminate the disadvantages of traditional manual CM approaches.-
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)-
dc.subject4605 Data Management and Data Science-
dc.subject46 Information and Computing Sciences-
dc.subject4014 Manufacturing Engineering-
dc.subject40 Engineering-
dc.subject9 Industry, Innovation and Infrastructure-
dc.titlePredictive Maintenance and Condition Monitoring in Machine Tools: An IoT Approach-
dc.typeArticle-
dc.date.updated2025-03-03T20:42:14Z-
dc.contributor.departmentMechanical Engineering-
dc.identifier.doihttps://doi.org/10.1109/iemtronics55184.2022.9795726-
Appears in Collections:Mechanical Engineering Publications

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