Predictive Maintenance in Manufacturing Using AI-Enhanced Big Data Analytics

Authors

  • Nirup Kumar Reddy Pothireddy  Independent Researcher, USA
  • Bipinkumar Reddy Algubelli  Independent Researcher, USA

DOI:

https://doi.org/10.32628/IJSRST2074281

Keywords:

Predictive Maintenance, Big Data Analytics, Artificial Intelligence, Machine Learning, Manufacturing Systems, Condition Monitoring, Equipment Prediction of Failure

Abstract

The AI integration of Industry 4.0 marked a breaking point as it comes to predictive maintenance for industry machinery systems. Traditional maintenance types predicting reactions to threats like maintenance downtime did not end up being effective in maintaining desired operational uptime, often causing revenue losses due to production delays, higher human error rates, and increased labor inputs. This paper outlines the predictive maintenance system summarized in brief as AI, using machine learning algorithms, toiling its way through the realm of data infrastructure to monitor health conditions of machines, recognize anomalies, and even "guess" failures before they take place. Using real-time sensor-generated data and/or historical machine logs, this machine has pattern types spelling out future breakdowns with the ability for intervention to be carried out quickly and with precision. The manuscript leans on the designing and testing of various predictive models such as random forests, support vector machines, and artificial neural networks trained on a full basket of high-dimensional data sets. This is an indication that the automated prediction framework is capable of achieving hard-to-envision high accuracy in predicting mechanical faults and time to fault (RUL), identifying practical validity. Each of the conclusions and discussions eloquently signs off on the stresses of its current experimentation while giving suggestions for possible directions for future work in smart predictive systems.

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International Journal of Scientific Research in Science and Technology

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Published

2016-05-25

Issue

Volume 2, Issue 3, May-June-2016

Section

Research Articles

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How to Cite

[1]
Nirup Kumar Reddy Pothireddy, Bipinkumar Reddy Algubelli "Predictive Maintenance in Manufacturing Using AI-Enhanced Big Data Analytics" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 2, Issue 3, pp.470-481, May-June-2016. Available at doi : https://doi.org/10.32628/IJSRST2074281