Andrianandrianina Johanesa, T.V.; Equeter, L.; Mahmoudi, S.A. Survey on AI Applications for Product Quality Control and Predictive Maintenance in Industry 4.0. Electronics2024, 13, 976.
Andrianandrianina Johanesa, T.V.; Equeter, L.; Mahmoudi, S.A. Survey on AI Applications for Product Quality Control and Predictive Maintenance in Industry 4.0. Electronics 2024, 13, 976.
Andrianandrianina Johanesa, T.V.; Equeter, L.; Mahmoudi, S.A. Survey on AI Applications for Product Quality Control and Predictive Maintenance in Industry 4.0. Electronics2024, 13, 976.
Andrianandrianina Johanesa, T.V.; Equeter, L.; Mahmoudi, S.A. Survey on AI Applications for Product Quality Control and Predictive Maintenance in Industry 4.0. Electronics 2024, 13, 976.
Abstract
Recent technological advancements such as IoT and Big Data have granted industries extensive access to data, opening up new opportunities for integrating Artificial Intelligence (AI) across various applications to enhance production processes. We can cite two critical areas where AI can play a key role in industry such as product quality control and predictive maintenance. This paper presents a survey of AI applications in the domain of Industry 4.0, with a specific focus on product quality control and predictive maintenance. Experiments were conducted using two datasets, incorporating different machine learning and deep learning models from the literature. Furthermore, this paper provides an overview of the AI solution development approach for product quality control and predictive maintenance. This approach includes several key steps, such as data collection, data analysis, model development, model explanation, and model deployment.
Keywords
Industry 4.0; Artificial Intelligence; Product quality control; Predictive maintenance
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
