Enhancing Production Efficiency Through Digital Twin Simulation Scheduling

Flexible custom manufacturing is becoming increasingly important, and, in the near future, it will serve as a key method to counter growing competition and meet market demands across most industrial sectors. This situation necessitates the substantial reorganization of companies’ material and inform...

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Main Authors: Patrik Grznár, Ladislav Papánek, Milan Marčan, Martin Krajčovič, Ivan Antoniuk, Štefan Mozol, Lucia Mozolová
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/7/3637
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author Patrik Grznár
Ladislav Papánek
Milan Marčan
Martin Krajčovič
Ivan Antoniuk
Štefan Mozol
Lucia Mozolová
author_facet Patrik Grznár
Ladislav Papánek
Milan Marčan
Martin Krajčovič
Ivan Antoniuk
Štefan Mozol
Lucia Mozolová
author_sort Patrik Grznár
collection DOAJ
description Flexible custom manufacturing is becoming increasingly important, and, in the near future, it will serve as a key method to counter growing competition and meet market demands across most industrial sectors. This situation necessitates the substantial reorganization of companies’ material and information flows, as traditional planning approaches focused on serial production and longer time horizons are gradually losing their effectiveness. An integrated digital twin system that unifies production and logistics planning is emerging as a promising solution. The proposed approach entails implementing a digital twin directly within custom manufacturing, enabling the continuous monitoring and real-time adjustment of production plans based on instant data from sensors and information systems. The system architecture is designed around multiple modules responsible for data collection and processing, scheduling, simulation, statistical analysis, and effective communication between the system and its users. By leveraging these components, the solution can flexibly adapt to any deviations or changes as they occur. Within the scope of this research, attention is devoted not only to the handling of dynamic and random data but also to the prioritization of individual orders. Equally emphasized is the role of intelligent communication tools, which promptly inform us about shifts in the production process and allow for rapid plan modifications to ensure the highest possible levels of efficiency and reliability.
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spelling doaj-art-73e5bf4cbb694e1ea82930b08369ffef2025-08-20T02:15:55ZengMDPI AGApplied Sciences2076-34172025-03-01157363710.3390/app15073637Enhancing Production Efficiency Through Digital Twin Simulation SchedulingPatrik Grznár0Ladislav Papánek1Milan Marčan2Martin Krajčovič3Ivan Antoniuk4Štefan Mozol5Lucia Mozolová6Department of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, SlovakiaDepartment of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, SlovakiaDepartment of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, SlovakiaDepartment of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, SlovakiaAsseco CEIT, a. s., Univerzitná 8661/6A, 010 08 Žilina, SlovakiaDepartment of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, SlovakiaDepartment of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina, Univerzitná 8215/1, 010 26 Žilina, SlovakiaFlexible custom manufacturing is becoming increasingly important, and, in the near future, it will serve as a key method to counter growing competition and meet market demands across most industrial sectors. This situation necessitates the substantial reorganization of companies’ material and information flows, as traditional planning approaches focused on serial production and longer time horizons are gradually losing their effectiveness. An integrated digital twin system that unifies production and logistics planning is emerging as a promising solution. The proposed approach entails implementing a digital twin directly within custom manufacturing, enabling the continuous monitoring and real-time adjustment of production plans based on instant data from sensors and information systems. The system architecture is designed around multiple modules responsible for data collection and processing, scheduling, simulation, statistical analysis, and effective communication between the system and its users. By leveraging these components, the solution can flexibly adapt to any deviations or changes as they occur. Within the scope of this research, attention is devoted not only to the handling of dynamic and random data but also to the prioritization of individual orders. Equally emphasized is the role of intelligent communication tools, which promptly inform us about shifts in the production process and allow for rapid plan modifications to ensure the highest possible levels of efficiency and reliability.https://www.mdpi.com/2076-3417/15/7/3637custom manufacturingdigital twinproduction planningreal-time adaptationdynamic data
spellingShingle Patrik Grznár
Ladislav Papánek
Milan Marčan
Martin Krajčovič
Ivan Antoniuk
Štefan Mozol
Lucia Mozolová
Enhancing Production Efficiency Through Digital Twin Simulation Scheduling
Applied Sciences
custom manufacturing
digital twin
production planning
real-time adaptation
dynamic data
title Enhancing Production Efficiency Through Digital Twin Simulation Scheduling
title_full Enhancing Production Efficiency Through Digital Twin Simulation Scheduling
title_fullStr Enhancing Production Efficiency Through Digital Twin Simulation Scheduling
title_full_unstemmed Enhancing Production Efficiency Through Digital Twin Simulation Scheduling
title_short Enhancing Production Efficiency Through Digital Twin Simulation Scheduling
title_sort enhancing production efficiency through digital twin simulation scheduling
topic custom manufacturing
digital twin
production planning
real-time adaptation
dynamic data
url https://www.mdpi.com/2076-3417/15/7/3637
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AT ivanantoniuk enhancingproductionefficiencythroughdigitaltwinsimulationscheduling
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