INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
The suggested predictive maintenance system makes use of sensor readings, operating conditions, and failure incidences from previous motor operation data. Machine learning models are trained on a large dataset, which enables them to identify patterns and correlations suggestive of possible motor breakdowns. A variety of algorithms are used to build a strong prediction model, including ensemble approaches, neural networks, and support vector machines. By continuously analysing real-time data from motors, the predictive maintenance model can identify possible flaws before they become serious failures. Because of this, maintenance teams may plan interventions during scheduled downtime, maximising the use of available resources and reducing unforeseen outages. By extending the lifespan of motors and lowering maintenance costs, the application of this predictive maintenance strategy supports overall sustainability initiatives.
"Predictive Maintenance of Motors using Machine Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.c430-c436, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404282.pdf
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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