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The manufacturing sector is experiencing a significant transformation through the integration of technologies such as Artificial Intelligence (AI), Predictive Maintenance (PdM), Big Data Analytics (BDA), and the Internet of Things (IoT), all anchored in Industry 4.0 principles. These cutting-edge technologies hold vast potential to improve efficiency, reduce downtime, and enhance product quality. Nevertheless, the complexity of manufacturing processes presents challenges like unpredictable machine behavior, interoperability issues, and difficulties in scaling AI-driven solutions. This thorough review investigates the developments in AI and PdM within the manufacturing field, highlighting the obstacles that obstruct seamless integration into manufacturing workflows. It points out the necessity for a hybrid model that merges synchronized machine processes with predictive abilities while ensuring adaptability and compatibility between systems. Additionally, the paper details current research challenges related to real-time processing, scalable frameworks, and privacy, aiming to create a more sustainable and resilient manufacturing environment.
Sharma et al. (Thu,) studied this question.
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