Artificial Intelligence-Driven Predictive Maintenance in Smart Manufacturing: A Deep Learning Approach to Industrial Automation
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V2I4P102Keywords:
Predictive maintenance, Deep learning, Data augmentation, Edge computing, Anomaly detection, IoT integration, Model interpretability, Federated learning, Automation, Digital twinsAbstract
Predictive maintenance (PdM) is a critical component of smart manufacturing, enabling industries to reduce downtime, optimize maintenance schedules, and enhance overall efficiency. This paper explores the application of deep learning techniques in PdM, focusing on how artificial intelligence (AI) can revolutionize industrial automation. We present a comprehensive review of the state-of-the-art in deep learning for PdM, discuss the challenges and opportunities, and propose a novel framework for implementing deep learning-based PdM systems. The paper includes case studies, algorithmic details, and future research directions to provide a holistic view of the topic
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References
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