Enhancing Industrial Process Optimization through Digital Twins

This paper explores the role of Digital Twins (DTs) in optimizing industrial processes, particularly in strategic sectors such as automotive, aerospace, and water treatment. With the growing need for companies to adapt to increased competition and technological advancements, DTs offer an innovative approach to process management. The study outlines the integration of real-time data analytics, machine learning, and IoT technologies into DT systems. It presents a detailed methodology for implementing DTs with statistical process control (SPC), focusing on a water filtration case study. The results demonstrate the DT’s ability to enhance operational efficiency, predict anomalies, and provide real-time monitoring and control through dynamic dashboards. This work highlights the importance of DTs in achieving intelligent, sustainable production, while addressing key challenges such as data integration and real-time synchronization.