Modeling and simulating production systems with a Digital Twin approach

In recent years, digital transformation has emerged as a fundamental trend in manufacturing industries, having a profound impact on factory processes and performance. One of the key technologies in this direction is the digital twin, which acts as a virtual, real-time version of physical systems and enables monitoring, analysis, and optimization of production processes with high accuracy and speed. Relying on real-time data obtained from sensors and Internet of Things (IoT) systems, the digital twin can simulate the status of equipment and production lines in real time and predict different scenarios for improving performance. This paper aims to provide a comprehensive perspective on the applications of digital twins in modeling and simulation of manufacturing systems. It first reviews the literature and previous research to review the current advances and challenges. It then introduces its research methodology by analyzing a manufacturing system in a hypothetical factory in which digital twin technology is used for monitoring and optimization. Finally, the results of the analysis show that this technology can help in faster and more accurate decision-making and increase productivity and quality of production by providing continuous improvement solutions. Therefore, suggestions are provided for the practical implementation of this framework in manufacturing industries, which can be a useful guide for managers and experts in the field of manufacturing.

کلیدواژه ها:

Digital twin ، manufacturing systems ، modeling ، simulation ، real-time decision making ، Industry ۴.۰