Design of Modular Automated Production Line for Classification, Palletizing and Storage
DOI:
https://doi.org/10.63688/qycftt93Keywords:
Industrial automation, flexible manufacturing, modular systems, plc simulation, automated logisticsAbstract
Industrial automation through flexible manufacturing systems (FMS) represents a key strategy to increase operational efficiency in logistics processes. The manufacturing industry faces the need to modernize classification, palletizing and storage processes to improve productivity and competitiveness. This study presents the design, simulation and cost estimation of a modular automated production line based on flexible manufacturing. The system was designed in three independent modules applying the Modular Function Deployment (MFD) approach, with central control using Siemens S7-1200 CPU 1215C PLC programmed in Ladder (LAD) and Function Block Diagram (FBD) according to IEC 61131-3 standard. Validation was performed through integrated simulation with Factory I/O, TIA Portal, PLCSIM and WinCC HMI. Simulation tests demonstrated correct integration of stations, validating control logic and cycle times. Palletizing of 24 boxes on pallet with four-layer patterns showed minor deviations (9-14%) compared to expected times. Preliminary economic estimation indicates a total cost of USD 351,925 divided into station components, control system, labor and distribution panel. The proposed modular design confirms efficiency, scalability and reliability of the system, constituting a comprehensive alternative for optimization of industrial logistics processes with flexible manufacturing approach.
References
Buzacott, J. A., & Yao, D. D. (1986). Flexible Manufacturing Systems: A Review of Analytical Models. Management Science, 32(7), 890–905. https://doi.org/10.1287/mnsc.32.7.890
Chan, F. T. S., Bhagwat, R., & Wadhwa, S. (2008). Comparative performance analysis of a flexible manufacturing system (FMS): a review-period-based control. International Journal of Production Research, 46(1), 1–24. https://doi.org/10.1080/00207540500521188
Dukkanci, O., Campbell, J. F., & Kara, B. Y. (2024). Facility location decisions for drone delivery: A literature review. European Journal of Operational Research, 316(2), 397–418. https://doi.org/10.1016/j.ejor.2023.10.036
Ellithy, K., Salah, M., Fahim, I. S., & Shalaby, R. (2024a). AGV and Industry 4.0 in warehouses: a comprehensive analysis of existing literature and an innovative framework for flexible automation. The International Journal of Advanced Manufacturing Technology, 134(1–2), 15–38. https://doi.org/10.1007/s00170-024-14127-0
Ellithy, K., Salah, M., Fahim, I. S., & Shalaby, R. (2024b). AGV and Industry 4.0 in warehouses: a comprehensive analysis of existing literature and an innovative framework for flexible automation. The International Journal of Advanced Manufacturing Technology, 134(1–2), 15–38. https://doi.org/10.1007/s00170-024-14127-0
Fuller, J. A., & Fortin, D. (1985). Management Information Systems: A Vehicle for Operations Management. International Journal of Operations & Production Management, 5(2), 58–62. https://doi.org/10.1108/eb054739
Neugebauer, R., Altan, T., Geiger, M., Kleiner, M., & Sterzing, A. (2006). Sheet metal forming at elevated temperatures. CIRP Annals, 55(2), 793–816. https://doi.org/10.1016/j.cirp.2006.10.008
Noroozi, A., Mazdeh, M. M., Heydari, M., & Rasti-Barzoki, M. (2018). Coordinating order acceptance and integrated production-distribution scheduling with batch delivery considering Third Party Logistics distribution. Journal of Manufacturing Systems, 46, 29–45. https://doi.org/10.1016/j.jmsy.2017.11.001
Plastria, F. (2024). Corrigendum to ‘How bad can the centroid be?’[Eur. J. Oper. Res. 252 (2016) 98–102]. European Journal of Operational Research, 313(2), 814–815. https://doi.org/10.1016/j.ejor.2023.10.022
Rueda-Carvajal, G. D., Tobar-Rosero, O. A., Sánchez-Zuluaga, G. J., Candelo-Becerra, J. E., & Flórez-Celis, H. A. (2025). Opportunities and Challenges of Industries 4.0 and 5.0 in Latin America. Sci, 7(2), 68. https://doi.org/10.3390/sci7020068
Schwörer, T., Jensen, M. B., Schou, C., Dueholm, B. C., Andersen, R., de Neergaard, W., Chrysostomou, D., Madsen, O., & Olesen, O. V. (2026). Modular and reconfigurable factories for continuous production innovation in pharmaceutical manufacturing. International Journal of Production Research, 64(6), 2210–2232. https://doi.org/10.1080/00207543.2025.2575844
Uhlmann, E., Saoji, M., & Peukert, B. (2016). Utilization of Thermal Energy to Compensate Quasi-static Deformations in Modular Machine Tool Frames. Procedia CIRP, 40, 1–6. https://doi.org/10.1016/j.procir.2016.01.037
Zhang, X., Ming, X., & Bao, Y. (2022). A flexible smart manufacturing system in mass personalization manufacturing model based on multi-module-platform, multi-virtual-unit, and multi-production-line. Computers & Industrial Engineering, 171, 108379. https://doi.org/10.1016/j.cie.2022.108379
Zheng, P., Yang, J., Lou, J., & Wang, B. (2024). Design and application of virtual simulation teaching platform for intelligent manufacturing. Scientific Reports, 14(1), 12895. https://doi.org/10.1038/s41598-024-62072-5
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Copyright (c) 2026 Juan Carlos Pisco Vanegas, Danner Anderson Figueroa Guerra, Samantha Marlene Puente Bosquez, Alan Ariel Arias Águila (Autor/a)
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