Enhancing Industrial Process Optimization through Digital Twins

Abstract

In this study, we focus on the role of digital twins (DTs) in industrial processes, concentrating on strategically important industries of automotive, aerospace and water treatment. In a context of increasing competition and rapid technological advances, DTs offer an innovative approach to the management of industrial operations. The study details how Internet of Things technologies (IoT), Artificial Intelligence (AI) algorithm and data analysis are integrated into DT systems. We also propose a detailed methodology for the implementation of DT combined with Statistical Process Control charts (SPC), which will be validated by a concrete application on a water filtration system. The results obtained thanks to this solution highlight the applicability of DT to optimise operational efficiency, anticipate anomalies and ensure real-time (RT) monitoring and control using dynamic dashboards. This study answers the question of the importance of implementing a DT solution to achieve intelligent and sustainable production, while addressing major challenges such as data integration and RT synchronisation.