Modeling the Wooden Pallet Manufacturing Process Using System Dynamics: A Case Study of the Voluntad de Dios Workshop in Buena Fe Canton

Authors

DOI:

https://doi.org/10.70577/asce.v5i3.1092

Keywords:

system dynamics; simulation; wooden pallets; production process; bottleneck.

Abstract

This study applied system dynamics to the wooden pallet manufacturing process at the Voluntad de Dios Workshop, located in Buena Fe Canton, Ecuador. The objective was to develop a simulation model to identify production constraints, evaluate improvement scenarios, and support decision-making. A mixed-methods approach, a non-experimental design, direct observation, and a time study based on 100 observations per workstation were employed. The model was developed using Vensim PLE 10.4, following Sterman’s methodology. The results identified assembly as the main bottleneck, with a standard time of 116.91 seconds, representing 68% of the total cycle time. An operational efficiency of 72.80% and 296.31 seconds of accumulated idle time per cycle at the cutting workstations were also determined. The model reproduced an output of 21 pallets per hour, equivalent to the observed production of 168 pallets per day. Among the scenarios evaluated, preventive maintenance provided the best balance between investment and return, with a projected monthly net profit of USD 4,409.20. Combining maintenance with an additional operator increased the projected net profit to USD 7,926.16 per month, subject to an adequate supply of raw materials. It is concluded that the model makes it possible to anticipate production constraints and support decisions aimed at improving production performance.

Downloads

Download data is not yet available.

References

Alanya-Rosenbaum, S., Bergman, R. D., & Gething, B. (2021). Assessing the life-cycle

environmental impacts of the wood pallet sector in the United States.

Antonelli, D., Litwin, P., & Stadnicka, D. (2018). Multiple System Dynamics and Discrete Event

Simulation for manufacturing system performance evaluation. Procedia CIRP, 78,

178–183. https://doi.org/10.1016/j.procir.2018.08.312 DOI: https://doi.org/10.1016/j.procir.2018.08.312

Fetene Adane, T., Bianchi, M. F., Archenti, A., & Nicolescu, M. (2019). Application of system

dynamics for analysis of performance of manufacturing systems. In Journal of

Manufacturing Systems (Vol. 53, pp. 212–233). Elsevier B.V.

https://doi.org/10.1016/j.jmsy.2019.10.004 DOI: https://doi.org/10.1016/j.jmsy.2019.10.004

Gejo-García, J., Reschke, J., Gallego-García, S., & García-García, M. (2022). Development of a

System Dynamics Simulation for Assessing Manufacturing Systems Based on the

Digital Twin Concept. Applied Sciences (Switzerland), 12(4).

https://doi.org/10.3390/app12042095 DOI: https://doi.org/10.3390/app12042095

Groesser, S. N., & Schaffernicht, M. (2012). Mental models of dynamic systems: Taking stock and DOI: https://doi.org/10.1007/978-1-4419-1428-6_1838

looking ahead. System Dynamics Review, 28(1), 46–68.

https://doi.org/10.1002/sdr.476 DOI: https://doi.org/10.1002/sdr.476

Hipólito, V., Álvaro, P., Karla, ;, & Alvarado Ramírez, M. (2018). HOME Revista ESPACIOS !

Evaluación de eficiencia y productividad de PyMEs productivas usando análisis

envolvente de datos e índice Malmquist Evaluation of efficiency and productivity of

productive SMEs using data envelopment analysis and Malmquist index (Vol. 39).

Hoffmann, J., Mai, C., Hu, B., & Buettner, R. (2025). A Systematic Literature Review on System

Dynamics. IEEE Access, 13, 88871–88887.

https://doi.org/10.1109/ACCESS.2025.3571620 DOI: https://doi.org/10.1109/ACCESS.2025.3571620

Kaur, G., & Kander, R. (2025). System Dynamics for Manufacturing: Supply Chain Simulation of

Hemp-Reinforced Polymer Composite Manufacturing for Sustainability.

Sustainability (Switzerland), 17(2). https://doi.org/10.3390/su17020765 DOI: https://doi.org/10.3390/su17020765

Kočí, V. (2019). Comparisons of environmental impacts between wood and plastic transport

pallets. Science of the Total Environment, 686, 514–528.

https://doi.org/10.1016/j.scitotenv.2019.05.472 DOI: https://doi.org/10.1016/j.scitotenv.2019.05.472

Lagarda-Leyva, E. A., Ruiz, A., & Morales-Mendoza, L. F. (2024). A System Dynamics Approach

to Valorize Overripe Figs in the Brewing of Artisanal Beer. Sustainability, 16(4),

1627. https://doi.org/10.3390/su16041627 DOI: https://doi.org/10.3390/su16041627

Mikati, N. (2010). Dependence of lead time on batch size studied by a system dynamics model.

International Journal of Production Research, 48(18), 5523–5532.

https://doi.org/10.1080/00207540903164628 DOI: https://doi.org/10.1080/00207540903164628

Poles, R. (2013). System Dynamics modelling of a production and inventory system for

remanufacturing to evaluate system improvement strategies. International Journal of

Production Economics, 144(1), 189–199. https://doi.org/10.1016/j.ijpe.2013.02.003 DOI: https://doi.org/10.1016/j.ijpe.2013.02.003

Romero, M., & Velasteguí, D. (2011). Descripción de las Cadenas Productivas de Madera en el

Ecuador Elaboración.

Rosova, A., Behun, M., Khouri, S., Cehlar, M., Ferencz, V., & Sofranko, M. (2022). Case study:

the simulation modeling to improve the efficiency and performance of production

process. Wireless Networks, 28(2), 863–872. https://doi.org/10.1007/s11276-020-

02341-z

Skoogh, A., Thürer, M., Subramaniyan, M., Matta, A., & Roser, C. (2023a). Throughput bottleneck

detection in manufacturing: a systematic review of the literature on methods and

operationalization modes. Production and Manufacturing Research, 11(1).

https://doi.org/10.1080/21693277.2023.2283031

Skoogh, A., Thürer, M., Subramaniyan, M., Matta, A., & Roser, C. (2023b). Throughput bottleneck

detection in manufacturing: a systematic review of the literature on methods and

operationalization modes. Production and Manufacturing Research, 11(1).

https://doi.org/10.1080/21693277.2023.2283031 DOI: https://doi.org/10.1080/21693277.2023.2283031

Sterman, J., Oliva, R., Linderman, K., & Bendoly, E. (2015). System dynamics perspectives and

modeling opportunities for research in operations management. In Journal of

Operations Management (Vols. 39–40, pp. 1–5). Elsevier B.V.

https://doi.org/10.1016/j.jom.2015.07.001 DOI: https://doi.org/10.1016/j.jom.2015.07.001

Tang, J., Dai, Z., Jiang, W., Wu, X., Zhuravkov, M. A., Xue, Z., & Wang, J. (2024). A

Comprehensive Review of Theories, Methods, and Techniques for Bottleneck

Identification and Management in Manufacturing Systems. In Applied Sciences

(Switzerland) (Vol. 14, Number 17). Multidisciplinary Digital Publishing Institute

(MDPI). https://doi.org/10.3390/app14177712 DOI: https://doi.org/10.3390/app14177712

Teunter, R. H., & Flapper, S. D. P. (2011). Optimal core acquisition and remanufacturing policies

under uncertain core quality fractions. European Journal of Operational Research,

210(2), 241–248. https://doi.org/10.1016/j.ejor.2010.06.015 DOI: https://doi.org/10.1016/j.ejor.2010.06.015

Tornese, F., Gnoni, M. G., Thorn, B. K., Carrano, A. L., & Pazour, J. A. (2021). Management and

logistics of returnable transport items: A review analysis on the pallet supply chain. In

Sustainability (Switzerland) (Vol. 13, Number 22). MDPI.

https://doi.org/10.3390/su132212747 DOI: https://doi.org/10.3390/su132212747

Published

2026-08-31

How to Cite

Villafuerte López , M. I., López Villacis , A. G., Barros Enríquez, J. D., & Avemañay Morocho , Ángel M. (2026). Modeling the Wooden Pallet Manufacturing Process Using System Dynamics: A Case Study of the Voluntad de Dios Workshop in Buena Fe Canton. ANNALS SCIENTIFIC EVOLUTION, 5(3), 2499–2523. https://doi.org/10.70577/asce.v5i3.1092

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.

Most read articles by the same author(s)