Keywords
layout planning
artificial intelligence
manufacturing system
How to Cite
Abstract
The paper presents production plant layout planning techniques on the basis of selected Digital Tools (DTs) utilization including generative artificial intelligence (AI). The authors studied possible techniques that can be used in production plant planning and researched their implementations on the basis of three defined production cells and lists of machine tools assigned to each cell. The usage of 2D and 3D Computer-Aided Design (CAD) software tools such as LibreCAD and FreeCAD was studied. The CAD software was applied for the design of layout using traditional CAD modelling procedures and also by the AI support. Moreover, MatlabTM software usage was presented as an alternative planning solution. It demonstrated opportunities resulting from automated code creation in the ChatGPTTM. The ChatGPTTM and Visual Studio CodeTM were applied as tools supporting the AI-assisted layout design methodology. The performed study revealed that artificial intelligence support and utilization of DTs may contribute to the production plant planning process by the collaborative implementation of various software DTs.
References
Autodesk Factory Design(TM). (2024). Make your next move toward modernized factory design. Retrieved December 12, 2024, from https://www.autodesk.com/solutions/factory-design
Bi, S., Shao, L., Zheng, J., & Yang, R. (2024). Workshop layout optimization method based on sparrow search algorithm: A new approach. Journal of Industrial and Production Engineering, 41(4), 324–343. https://doi.org/10.1080/21681015.2024.2302630
CampusAI. (2025). CampusAI Human + AI Collaboration. Retrieved March 12, 2025, from https://campusai.pl
Chao, L., Shuang, L., Wang, S., & Cai, B. (2015). Research on automatic layout planning and performance analysis system of production line based on simulation. In Proceedings of China Modern Logistics Engineering. Lecture Notes in Electrical Engineering (vol. 286, pp. 455-462). Springer. https://doi.org/10.1007/978-3-662-44674-4_42
ChatGPT(TM). (2024). ChatGPT by OpenAI. Retrieved December 21, 2024, from https://chatgpt.com
ChatGPT(TM). (2025a). Chat in ChatGPT(TM) no. 1. Retrieved March 12, 2025, from https://chatgpt.com/share/67ac7196-d1b0-800c-84e0-11d54e80af84
ChatGPT(TM). (2025b). Chat in ChatGPT(TM) no. 2. Retrieved March 12, 2025, from https://chatgpt.com/share/67ac7397-eec0-800c-ad63-9357695e9e4e
ChatGPT(TM). (2025c). Chat in ChatGPT(TM) no. 3. Retrieved March 12, 2025, from https://chatgpt.com/share/67ac7592-80f0-800c-89b0-01827945a13a
Dassault Systèmes. (2024). DELMIA 3D Virtual Factory. Retrieved December 12, 2025, from https://discover.3ds.com/pl/delmia-digital-manufacturing-software
Disselkamp, J.-P., Kürpick, D., Schütte, B., Hovemann, A., & Dumitrescu, R. (2024). Use cases of generative AI in factory planning: potential and challenges. In J. Malmqvist, M. Candi, R. J. Saemundsson, F. Bystrom, & O. Isaksson (Eds.), Proceedings of NordDesign 2024 (pp. 1-10). Fraunhofer IEM. https://doi.org/10.35199/NORDDESIGN2024.22
Elbasheer, M., Longo, F., Nicoletti, L., Padovano, A., Solina, V., & Vetrano, M. (2022). Applications of ML/AI for decision-intensive tasks in production planning and control. Procedia Computer Science, 200, 1903–1912. https://doi.org/10.1016/j.procs.2022.01.391
Fang-ying, C., Jian-feng, L., & Hao, Z. (2010). Factory planning and digital factory. In 2010 International Conference on Audio, Language and Image Processing (pp. 499–502). IEEE. https://doi.org/10.1109/ICALIP.2010.5684524
FreeCAD. (2024). FreeCAD Your own 3D parametric modeller. Retrieved December 12, 2024, from https://www.freecad.org/
Janecki, L., Reh, D., & Arlinghaus, J. C. (2024). Challenges of quality assurance in early planning and ramp up of production facilities—potentials of planning automation via virtual engineering. Procedia Computer Science, 232, 2498–2507. https://doi.org/10.1016/j.procs.2024.02.068
Lenin, N., Siva Kumar, M., Islam, M. N., & Ravindran, D. (2013). Multi-objective optimization in single-row layout design using a genetic algorithm. The International Journal of Advanced Manufacturing Technology, 67(5–8), 1777–1790. https://doi.org/10.1007/s00170-012-4608-z
Li, B. h., Hou, B. c., Yu, W. t., Lu, X. b., & Yang, C. w. (2017). Applications of artificial intelligence in intelligent manufacturing: a review. Frontiers of Information Technology & Electronic Engineering, 18, 86–96. https://doi.org/10.1631/FITEE.1601885
LibreCAD. (2024). LibreCAD. Open Source 2D-CAD. Retrieved December 21, 2024, from https://librecad.org
Lin, M.-H., & Fu, L.-C. (2001). A virtual factory based approach to on-line simulation and scheduling for an FMS and a case study. Journal of Intelligent Manufacturing, 12, 269–279. https://doi.org/10.1023/A:1011201009821
Lindskog, E., Vallhagen, J., Berglund, J., & Johansson, B. (2016). Improving lean design of production systems by visualization support. Procedia CIRP, 41, 602–607. https://doi.org/10.1016/j.procir.2016.01.004
Matlab(TM). (2024). Welcome to Matlab. Retrieved December 21, 2024, from https://matlab.mathworks.com
Mengzhen, X., Yong, W., Haigen, Y., Lei, W., Longbao, H., Hongyan, Y., Wenting, X., & Jun, M. (2019). Simulation and optimization of intelligent workshop layout and logistics transportation by system layout planning combined with Em-plant. In 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS) (pp. 663–667). https://doi.org/10.1109/ICSESS47205.2019.9040788
Python. (2024). Python. Retrieved December 21, 2024, from https://www.python.org
Schäfer, L., Klenk, F., Maier, T., Zehner, M., Peukert, S., Linzbach, R., Treiber, T., & Lanza, G. (2024). A systematic approach for simulation-based dimensioning of production systems during the concept phase of factory planning. Production Engineering, 18, 813-825. https://doi.org/10.1007/s11740-024-01273-3
Siemens. (2024). TECNOMATIX Plant Simulation. Retrieved December 12, 2024, from https://plm.sw.siemens.com/pl-PL/tecnomatix/plant-simulation-software
Tearwattanarattikal, P., Namphacharoen, S., & Chamrasporn, C. (2008). Using ProModel as a simulation tools to assist plant layout design and planning: Case study plastic packaging factory. Songklanakarin Journal of Science and Technology, 30(1), 117–123.
Terkaj, W., Tolio, T., & Urgo, M. (2015). A virtual factory approach for in situ simulation to support production and maintenance planning. CIRP Annals, 64(1), 451–454. https://doi.org/10.1016/j.cirp.2015.04.121
Vernadat, F. (2020). Enterprise modelling: Research review and outlook. Computers in Industry, 122, Article 103265. https://doi.org/10.1016/j.compind.2020.103265
Visual Studio Code(TM). (2024). Your code editor. Redefined with AI. Retrieved December 21, 2024, from https://code.visualstudio.com
Wan, J., Li, X., Dai, H. -N., Kusiak, A., Martínez-García, M., & Li, D. (2021). Artificial-intelligence-driven customized manufacturing factory: Key technologies, applications, and challenges, In Proceedings of the IEEE (vol. 109, no. 4, pp. 377–398). https://doi.org/10.1109/JPROC.2020.3034808
Wang, H., Wang, C., Liu, Q., Zhang, X., Liu, M., Ma, Y., Yan, F., & Shen, W. (2024). A data and knowledge driven autonomous intelligent manufacturing system for intelligent factories, Journal of Manufacturing Systems, 74, 512–526, https://doi.org/10.1016/j.jmsy.2024.04.011
Zhang, Z., Wang, X., Wang, X., Cui, F., & Cheng, H. (2019). A simulation-based approach for plant layout design and production planning. Journal of Ambient Intelligence and Humanized Computing, 10(3), 1217–1230. https://doi.org/10.1007/s12652-018-0687-5