Soutenance de thèse : Xeniya PYSTINA 

« Systèmes de Jumeau Numérique pour les systèmes de production : application sur le manufacturing lab »

Doctorante : Xeniya PYSTINA 

Laboratoire INSA : DISP

École doctorale : ED512 : InfoMaths (Informatique et Mathématiques de Lyon)

Traditional production systems face major challenges in transitioning to Industry 4.0 (I4.0). These systems must quickly adapt to fluctuations in demand, supply chain disruptions, and equipment failures. Digitalizing company assets is crucial for seamless communication and data integration across value chains. This transformation requires reorganizing machines and equipment using technologies such as the Internet of Things (IoT), data analytics, and artificial intelligence. Modern production systems, incorporating I4.0 concepts, rely on advanced architectures like RAMI4.0 for designing and implementing Digital Twins (DT).
For these systems to operate effectively in smart production environments, they must meet interoperability, communication, and standardization requirements. However, consistent application of standards, such as ISO 23247, remains a significant challenge. Managing intelligent production systems involves addressing complex structural, operational, and organizational issues. A methodical, integrated approach is essential to align strategic objectives with field operations.
This research aims to develop a structured approach for designing, developing, and implementing DT systems aligned with companies' strategic visions and commercial goals in manufacturing industries. The approach ensures traceability of design attributes, data interoperability, real-time synchronization, and model accuracy, adapting standard DT definitions to meet specific business needs.
The framework is divided into two main parts: (1) Developing a DT system on a smart platform to test various scenarios, such as production order management and rescheduling, considering the production line hierarchy; and (2) Validating the conceptual framework by designing a DT system prototype. This approach provides recommendations on how to develop and use DTs to enhance production system performance and strategic objectives, addressing the challenges of modern production systems.