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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
Predictive Maintenance for Manufacturing Systems
Authors
Avi Singh, Nitya Jain, Preet Kamal
Keywords
LSTM networks, time-series analysis, predictive modelling, fault detection, smart manufacturing, AI-driven maintenance, equipment monitoring.
Abstract
This paper investigates the effects of Long Short-Term Memory networks in predictive maintenance of manufacturing systems. The proposed framework improves on prediction from failure and anomalous detection because LSTMs have the ability to deal with time series data. These IoT qualified sensors equipped with real time machine health monitoring and the supportof AI driven analytics along with historical patterns to forecast potential breakdowns form the bedrock for the work. LSTM predictive maintenance strategies, integrated with the maintenance strategies, result in minimum sudden downtime, maximum asset reliability and maximum efficiency of industrial operation. This study proposes deep learning for proactive maintenance in order to redefine the traditional maintenance methods and make the smart manufacturing practices.
IJCRT's Publication Details
Unique Identification Number - IJCRT25A4284
Paper ID - 282155
Page Number(s) - k987-k999
Pubished in - Volume 13 | Issue 4 | April 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Avi Singh, Nitya Jain, Preet Kamal, "Predictive Maintenance for Manufacturing Systems", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 4, pp.k987-k999, April 2025, Available at :http://www.ijcrt.org/papers/IJCRT25A4284.pdf
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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