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

Junaid Iqbal

doi:10.55524/ijircst.2022.10.4.11

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.

Keywords

Machine failures, Preventive maintenance, RUL, RNN

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Cites this article as

[Junaid Iqbal, Krishna Tomar (2022), Predictive Maintenance of Machines on Large Scale Industrial Units Using Machine Learning, International Journal of Innovative Research in Computer Science & Technology (IJIRCST), Vol-10, Issue-4, Page No-92-101], (ISSN 2347 - 5552). www.ijircst.org

Corresponding Author

Junaid Iqbal

M. Tech, Power System, Department of Electrical Engineering, RIMT University, Punjab, India

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