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Open Access Journal Article

Adaptive Neuro-Fuzzy Inference Systems for Predictive Maintenance in Manufacturing

by James Martin 1,*
1
James Martin
*
Author to whom correspondence should be addressed.
TASC  2019, 4; 1(1), 4; https://doi.org/10.69610/j.tasc.20191130
Received: 27 September 2019 / Accepted: 29 October 2019 / Published Online: 30 November 2019
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Abstract

This paper presents a novel approach to predictive maintenance in manufacturing using Adaptive Neuro-Fuzzy Inference Systems (ANFIS). As the heart of industrial processes, predictive maintenance is crucial in ensuring the optimal performance and reducing the downtime of manufacturing systems. Traditional methods often suffer from the limitations of being data-intensive and computationally expensive. The ANFIS model offers a promising solution by integrating the strengths of neural networks and fuzzy logic, which allows for the modeling of complex, nonlinear relationships in manufacturing systems. The paper details the methodology for designing and implementing an ANFIS for predictive maintenance. It outlines the steps involved in data preprocessing, feature selection, and the construction of the ANFIS model. Through a series of simulations and case studies, the effectiveness of the proposed ANFIS model is demonstrated in accurately predicting equipment failures and optimizing maintenance schedules. The results indicate that the ANFIS-based approach can significantly decrease maintenance costs and improve the reliability of manufacturing systems.

Keywords: Predictive Maintenance, - Adaptive Neuro-Fuzzy Inference Systems (ANFIS), - Manufacturing Systems, - Data-Driven Modeling, - Equipment Reliability.;
Copyright: © 2019 by Martin. 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
Martin, J. Adaptive Neuro-Fuzzy Inference Systems for Predictive Maintenance in Manufacturing. Transactions on Applied Soft Computing, 2019, 1, 4. https://doi.org/10.69610/j.tasc.20191130
AMA Style
Martin J. Adaptive Neuro-Fuzzy Inference Systems for Predictive Maintenance in Manufacturing. Transactions on Applied Soft Computing; 2019, 1(1):4. https://doi.org/10.69610/j.tasc.20191130
Chicago/Turabian Style
Martin, James 2019. "Adaptive Neuro-Fuzzy Inference Systems for Predictive Maintenance in Manufacturing" Transactions on Applied Soft Computing 1, no.1:4. https://doi.org/10.69610/j.tasc.20191130
APA style
Martin, J. (2019). Adaptive Neuro-Fuzzy Inference Systems for Predictive Maintenance in Manufacturing. Transactions on Applied Soft Computing, 1(1), 4. https://doi.org/10.69610/j.tasc.20191130

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