Smart Factories in the Era of Industry 4.0: Convergence of IoT and Cyber-Physical Systems for Intelligent Automation, Connectivity, and Resilient Manufacturing

K. P. Arjun () and V. Smitha
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K. P. Arjun: LEAD College (Autonomous)
V. Smitha: DCMAT

A chapter in Proceedings of the International Conference on Operations & Supply Chain Management 2025 (ICOSCM 2025), 2025, pp 261-270 from Springer

Abstract: Abstract The convergence of Internet of Things (IoT) and Cyber-Physical Systems (CPS) represents a transformative paradigm in modern manufacturing, establishing the foundation for Industry 4.0 smart factories. This paper presents a comprehensive framework for intelligent automation that integrates real-time data acquisition, predictive analytics, and adaptive control mechanisms to enhance manufacturing efficiency and resilience. We propose a hierarchical architecture comprising five interconnected layers addressing sensing and actuation, edge computing, fog computing, cloud analytics, and enterprise integration. Our framework addresses critical challenges including interoperability, security, scalability, and real-time decision-making. Through simulation studies and theoretical analysis using real-world manufacturing datasets totaling over 10 million data points, we demonstrate that the proposed framework achieves 34% improvement in Overall Equipment Effectiveness (OEE), 42% reduction in unplanned downtime, and 28% enhancement in energy efficiency compared to traditional manufacturing systems. The research contributes a novel multi-agent coordination protocol employing game-theoretic consensus mechanisms for distributed manufacturing environments and introduces adaptive ensemble machine learning algorithms achieving 94.8% accuracy in predictive maintenance. Implementation considerations, including comprehensive cybersecurity measures and standardization requirements, are thoroughly examined to facilitate practical deployment in industrial settings.

Keywords: Industry 4.0; Smart Manufacturing; Cyber-Physical Systems; Internet of Things; Intelligent Automation; Digital Twin; Predictive Maintenance (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-914-8_17

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