Authors :
Jesu Narkarunai Arasu Malaiyappan; Gowrisankar Krishnamoorthy; Suhas Jangoan
Volume/Issue :
Volume 9 - 2024, Issue 3 - March
Google Scholar :
https://tinyurl.com/563kkurd
Scribd :
https://tinyurl.com/yeshrbyd
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAR984
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The use of predictive maintenance Machine
learning techniques aid systems or machines in lowering
the occurrence of certain types of machine failures via
prediction and the use of specific methods. An essential
tactic for improving the efficiency and reliability of
industrial equipment and optimizing maintenance
operations is predictive maintenance (PdM). Machine
learning-based predictive maintenance helps businesses
reduce unscheduled downtime, maintenance expenses,
and operational efficiency by identifying and fixing
potential equipment issues in advance.
Keywords :
Machine Learning, Jupiter, Proactive, Nonintrusive, Vibration, and Predictive Maintenance.
The use of predictive maintenance Machine
learning techniques aid systems or machines in lowering
the occurrence of certain types of machine failures via
prediction and the use of specific methods. An essential
tactic for improving the efficiency and reliability of
industrial equipment and optimizing maintenance
operations is predictive maintenance (PdM). Machine
learning-based predictive maintenance helps businesses
reduce unscheduled downtime, maintenance expenses,
and operational efficiency by identifying and fixing
potential equipment issues in advance.
Keywords :
Machine Learning, Jupiter, Proactive, Nonintrusive, Vibration, and Predictive Maintenance.
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