Dr. Matevž Resman, doc. dr. Mihael Debevec, univ. dipl. inž., doc. dr. Marko Šimic, univ. dipl. inž., prof. dr. Niko Herakovič, univ. dipl. inž., vsi Univerza v Ljubljani, fakulteta za strojništvo

Povzetek:
Digital twins are emerging as a cornerstone technology in the framework of Industry 4.0, providing a transformative means to optimize manufacturing processes, enhance flexibility, and respond effectively to the dynamic changes in industrial environments. These virtual replicas of physical systems enable organizations to transition from traditional manufacturing paradigms to smart factories, leveraging data-driven insights and real-time operational capabilities.
The proposed five-step methodology offers a structured and universal approach to the development and implementation of digital twins, suitable for businesses of all sizes. This methodology facilitates the systematic transformation of production systems and ensures their alignment with the demands of modern, intelligent manufacturing. The steps include:
1. System Classification: Identifying and categorizing the elements within the manufacturing system that will form the foundation of the digital twin. 2. Functional Diagram Design: Developing a conceptual framework that outlines the functionality and interactions within the system. 3. Digital Model Development: Creating a detailed digital representation of the system, capturing its structure, behavior, and operational dynamics. 4. Integration of Real-Time Data: Enabling dynamic interaction between the digital twin and live operational data to ensure accuracy and relevance. 5. Visualization and Interaction: Providing real-time visualization tools tailored to the needs of various stakeholders, enhancing usability, transparency, and decision-making efficiency.
By following these stages, companies can achieve a comprehensive understanding of their processes, leading to significant improvements in competitiveness, cost reduction, and sustainability. The integration of digital twins facilitates advanced simulation and analysis, supporting informed decision-making at all levels of production. Furthermore, real-time visualization capabilities allow the system to adapt to diverse user requirements, thereby boosting operational efficiency and system transparency.
This methodology not only addresses the contemporary challenges of the industrial sector but also lays a robust foundation for future innovation within smart factories. As a tool for digital transformation, it underscores the pivotal role of digital twins in advancing manufacturing systems, ensuring their alignment with the evolving landscape of Industry 4.0.

Keywords:
methodology, agile factories, smart factories, green transformation, energy efficiency, social responsibility​

Acknowledgement:
The work was financially supported in the framework of the Slovenian Research and Innovation Agency – ARIS, Research Programme P2-0248 – Innovative manufacturing systems and processes, research project J2-4470 – Research on the reliability and efficiency of edge computing in a smart factory using 5G technologies. The work was funded by the European Union, project 101087348 – Strengthening the capacity for excellence of Slovenian and Croatian innovation ecosystems to support the digital and green transitions of maritime regions and project 101058693 – Sustainable Transition to the Agile and Green Enterprise (STAGE Project).​