Download PDFOpen PDF in browserImplementation of Internet of Things (IoT) in Manufacturing OperationsEasyChair Preprint 1417619 pages•Date: July 26, 2024AbstractThe implementation of the Internet of Things (IoT) in manufacturing operations represents a transformative advancement in industrial practices, driving increased efficiency, productivity, and innovation. IoT integrates a network of interconnected devices, sensors, and systems that communicate and exchange data in real-time, providing manufacturers with unprecedented visibility and control over their operations.
This abstract outlines the significant benefits of IoT in manufacturing, including predictive maintenance, which utilizes real-time sensor data to anticipate equipment failures and reduce downtime. It also highlights the role of IoT in enhancing quality control through automated inspection systems and real-time monitoring, thereby improving product standards and reducing defects. Additionally, IoT enables more efficient supply chain management by offering real-time tracking and automated replenishment, optimizing inventory levels and reducing operational costs.
The implementation of IoT requires a strategic approach, beginning with a thorough assessment of manufacturing needs and goals. Key considerations include selecting appropriate technology, integrating IoT systems with existing infrastructure, and ensuring robust data management and security. Effective implementation also necessitates comprehensive training and change management to adapt to new technologies and workflows.
While the potential of IoT in manufacturing is vast, it is not without challenges. Issues such as integration with legacy systems, data security, and scalability must be addressed to fully leverage IoT’s capabilities. Through case studies and industry examples, this abstract explores successful implementations and common obstacles, providing insights into effective strategies for overcoming these challenges. Keyphrases: Internet of Things (IoT), Predictive Maintenance, Supply Chain Management, process optimization, quality control
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