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Open Access Journal Article

Predictive Maintenance in Industrial IoT Using Time-Series Analysis and Machine Learning

by David Anderson 1,*
1
David Anderson
*
Author to whom correspondence should be addressed.
TASC  2023, 42; 5(2), 42; https://doi.org/10.69610/j.tasc.20230922
Received: 21 July 2023 / Accepted: 24 August 2023 / Published Online: 22 September 2023
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Abstract

The integration of the Industrial Internet of Things (IIoT) has revolutionized the industrial sector by enabling the collection and analysis of vast amounts of data from various industrial processes. One of the key applications of this technology is predictive maintenance, which aims to minimize downtime and maximize the operational efficiency of industrial equipment through early detection of potential failures. This paper focuses on the application of time-series analysis and machine learning techniques to enhance the predictive maintenance capabilities in the context of IIoT. By leveraging the temporal patterns and trends present in the data, we propose a novel approach that integrates both statistical and machine learning algorithms to predict the likelihood of equipment failure. The effectiveness of our method is demonstrated through a case study in a manufacturing plant, where the results indicate a significant reduction in maintenance costs and increased equipment reliability. The study highlights the potential of combining time-series analysis and machine learning for predictive maintenance in the IIoT era.

Keywords: Predictive Maintenance, Industrial IoT, Time-Series Analysis, Machine Learning, Equipment Reliability.;
Copyright: © 2023 by Anderson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Anderson, D. Predictive Maintenance in Industrial IoT Using Time-Series Analysis and Machine Learning. Transactions on Applied Soft Computing, 2023, 5, 42. https://doi.org/10.69610/j.tasc.20230922
AMA Style
Anderson D. Predictive Maintenance in Industrial IoT Using Time-Series Analysis and Machine Learning. Transactions on Applied Soft Computing; 2023, 5(2):42. https://doi.org/10.69610/j.tasc.20230922
Chicago/Turabian Style
Anderson, David 2023. "Predictive Maintenance in Industrial IoT Using Time-Series Analysis and Machine Learning" Transactions on Applied Soft Computing 5, no.2:42. https://doi.org/10.69610/j.tasc.20230922
APA style
Anderson, D. (2023). Predictive Maintenance in Industrial IoT Using Time-Series Analysis and Machine Learning. Transactions on Applied Soft Computing, 5(2), 42. https://doi.org/10.69610/j.tasc.20230922

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