The Role of Edge Computing in Enhancing Real-Time Data Processing for Smart Manufacturing

Abstract

Smart manufacturing is transforming the industrial sector with the use of cutting-edge technologies like artificial intelligence (AI), big data analytics, and the Internet of Things (IoT) to increase efficiency, flexibility, and decision-making. However, because to their inability to manage the fast flow of data, traditional centralized systems experience latency problems that impede real-time processing. By reducing latency, improving data security, enabling data processing nearer to the source, and boosting operational efficiency, edge computing offers a solution. This study explores the ways in which edge computing might facilitate real-time data processing for smart manufacturing applications in supply chain optimization, quality assurance, and predictive maintenance. Edge computing facilitates smooth and robust production processes by providing immediate analysis and reaction to high-frequency, changeable data streams from IoT sensors, enabling quick reactions to changing circumstances. In order to improve the overall effectiveness and responsiveness of smart manufacturing systems, this study offers a paradigm for comprehending how edge computing might handle the issues of data volume, interaction with legacy systems, and network stability.