Evaluation of production line expansion efficiency using computer simulation

被引:0
作者
Poloczek, Roksana [1 ]
Oleksiak, Beata [1 ]
机构
[1] Silesia Univ Technol, Krasinskiego St 8, PL-40019 Katowice, Poland
关键词
computer simulation; process optimization; production efficiency; process modeling; workflow;
D O I
10.30657/pea.2024.30.48
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The article discusses the application of computer simulation in the optimization of production processes, particularly in the context of analyzing scenarios related to the addition of new production lines. The conducted research and simulations have shown that computer simulation is a key tool for precise modeling and analysis of various options, allowing for better understanding and optimization of production activities. The article presents the theoretical foundations of simulation along with practical examples of its application, focusing on assessing the impact of different production line configurations on the overall system's efficiency. The analysis of benefits includes shortening the production cycle time, increasing flexibility, and improving operational efficiency. The challenges associated with implementing computer simulation, such as the need for specialized knowledge and the necessity for continuous updates of simulation models, are also discussed. Based on the research and analyses conducted, the article demonstrates that computer simulation is an effective tool supporting strategic and operational decision-making in production management, particularly in the context of expanding production infrastructure.
引用
收藏
页码:520 / 527
页数:8
相关论文
共 26 条
[1]  
Attaran M., 2022, Advances in Computational Intelligence, DOI [10.1007/s00542-021-06244-3, DOI 10.1007/S00542-021-06244-3]
[2]  
Banks J., 2010, Discrete-event System Simulation
[3]   A conceptual architecture and model for smart manufacturing relying on service-based digital twins [J].
Catarci, Tiziana ;
Firmani, Donatella ;
Leotta, Francesco ;
Mandreoli, Federica ;
Mecella, Massimo ;
Sapio, Francesco .
2019 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (IEEE ICWS 2019), 2019, :229-236
[4]  
Chen R., 2022, Processes, V10, P589, DOI [10.3390/pr10040589, DOI 10.3390/PR10040589]
[5]   DT-II:Digital twin enhanced Industrial Internet reference framework towards smart manufacturing [J].
Cheng, Jiangfeng ;
Zhang, He ;
Tao, Fei ;
Juang, Chia-Feng .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2020, 62
[6]   Digital twin-enabled smart industrial systems: a bibliometric review [J].
Ciano, Maria Pia ;
Pozzi, Rossella ;
Rossi, Tommaso ;
Strozzi, Fernanda .
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2021, 34 (7-8) :690-708
[7]   Review of digital twin applications in manufacturing [J].
Cimino, Chiara ;
Negri, Elisa ;
Fumagalli, Luca .
COMPUTERS IN INDUSTRY, 2019, 113
[8]   Simulation-based decision support tool for in-house logistics: the basis for a digital twin [J].
Coelho, F. ;
Relvas, S. ;
Barbosa-Povoa, A. P. .
COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 153
[9]   A simulation-based scheduling system for real-time optimization and decision making support [J].
Frantzen, Marcus ;
Ng, Amos H. C. ;
Moore, Philip .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2011, 27 (04) :696-705
[10]  
Gao Y., 2023, Simulation-Based Manufacturing System Design and Analysis, DOI [10.1007/978-981-16-9590-3, DOI 10.1007/978-981-16-9590-3]