Predictive Maintenance of Machines on Large Scale Industrial Units Using Machine Learning

Authors

  • Junaid Iqbal M. Tech, Power System, Department of Electrical Engineering, RIMT University, Punjab, India Author
  • Krishna Tomar Assisstant Professor, Department of Electrical Engineering, RIMT University, Punjab, India Author

DOI:

https://doi.org/10.55524/

Keywords:

Machine failures, Preventive maintenance, RUL, RNN

Abstract

Anticipating machine breakdowns is one  of Industry 4.0's primary goals. It's critical to be able to  prevent failures since downtime costs money and results in  a loss of productivity. That's why it's critical for machine  maintenance to figure out how many cycles or RULs are  left till the breakdown occurs. The And where ever  possible, RUL estimations should have been based on  previous direct observation under the same circumstance.  The construction of tracking the present status of  technology is at the heart of RUL estimation technology.  While there has been a lot of study done on this subject,  there is no one-size-fits-all solution. This method, which  makes use of nn (RNN) to solve problems, predictive  maintenance of the proposed solution, is motivated by the lack of a universal technique. 

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Published

2022-07-30

Issue

Vol. 10 No. 4 (2022): International Journal of Innovative Research in Computer Science and Technology (July) 2022

Section

Articles

How to Cite

Predictive Maintenance of Machines on Large Scale Industrial Units Using Machine Learning . (2022). International Journal of Innovative Research in Computer Science & Technology, 10(4), 92–101. https://doi.org/10.55524/
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