Digital Twins for Operations and Supply Chain Management from Data Engineering Point of View

Digital Twins (DTs) have emerged as a powerful technology that enables manufacturing companies to build virtual representations of physical systems or assets, allowing them to monitor, analyze, and optimize their Operations for Supply Chain Management (OSCM) systems. By leveraging the capabilities of data analytics, IoT sensors, and cloud computing, digital twins can help organizations gain insight into their manufacturing operations and supply chain networks, improve production efficiency, reduce downtime, and enhance overall customer satisfaction. Although the potential benefits of DTs are widely acknowledged, little attention has been paid to the examination of the Data Infrastructure (DI) of these tools, which is a critical aspect of their successful implementation. A systematic and comprehensive understanding of the data sources, data warehousing, data integration, and data analytics techniques used in OSCM-related DT applications is essential for realizing their full potential. Consequently, this article provides a high-level introduction to the main DI components of DT applied to OSCM