Publicado

2019-01-01

Picking planning and quality control analysis using discrete simulation: case in a food industry

Planificación de picking y análisis de control de calidad mediante simulación discreta: caso en una industria alimentaria

DOI:

https://doi.org/10.15446/dyna.v86n208.76105

Palabras clave:

discrete simulation, picking policies, quality control, food industry (en)
simulación discreta, políticas de picking, control de calidad, industria alimentaria (es)

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Autores/as

In warehouse operations management, picking is one of the most expensive and time-consuming activities; its impact can be seen in the final product delivered to clients, affecting logistic Key Performance Indicators and level of service. On the other hand, changes in picking policy and quality control are challenging to implement in a real-world context. In this paper, we used a simulation methodology to determine the best flow of products and the optimum ratio of the sample in control quality. Simulation has been shown as an useful tool for industrial engineering to determine the best flow and bottlenecks inside the warehouse. This paper found significant improvements when the proposed changes in the picking policy and quality control methods were simulated. Our research also showed that the sampling quality control brings substantial gains to the queuing time, while nonetheless maintaining the desirable quality.

Además de ser es una de las actividades más caras y lentas de las operaciones que se gestionan dentro de los almacenes, la preparación de los pedidos o picking impacta el producto final entregado a los clientes, afectando los indicadores de rendimiento logísticos y el nivel de servicio. La elección de una política adecuada de picking, y el control de su desempeño y calidad constituyen desafíos importantes en un contexto real. Numerosos estudios han demostrado que la simulación es una herramienta útil en ingeniería industrial para estudiar los flujos de productos y eliminar los cuellos de botella en almacenes. Es por eso que este trabajo se apoya sobre la simulación para determinar el mejor flujo de productos y la política de muestreo óptima para el control de la calidad. Así, los experimentos de simulación demuestran que los cambios de política propuestos para las actividades de picking y los métodos de muestreado conducen a mejoras significativas, particularmente en el caso de los tiempos de espera, manteniendo la calidad deseada.

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Cómo citar

IEEE

[1]
F. Z. L. Bastos, C. T. Scarpin, y J. E. Pécora Junior, «Picking planning and quality control analysis using discrete simulation: case in a food industry», DYNA, vol. 86, n.º 208, pp. 271–280, ene. 2019.

ACM

[1]
Bastos, F.Z.L., Scarpin, C.T. y Pécora Junior, J.E. 2019. Picking planning and quality control analysis using discrete simulation: case in a food industry. DYNA. 86, 208 (ene. 2019), 271–280. DOI:https://doi.org/10.15446/dyna.v86n208.76105.

ACS

(1)
Bastos, F. Z. L.; Scarpin, C. T.; Pécora Junior, J. E. Picking planning and quality control analysis using discrete simulation: case in a food industry. DYNA 2019, 86, 271-280.

APA

Bastos, F. Z. L., Scarpin, C. T. & Pécora Junior, J. E. (2019). Picking planning and quality control analysis using discrete simulation: case in a food industry. DYNA, 86(208), 271–280. https://doi.org/10.15446/dyna.v86n208.76105

ABNT

BASTOS, F. Z. L.; SCARPIN, C. T.; PÉCORA JUNIOR, J. E. Picking planning and quality control analysis using discrete simulation: case in a food industry. DYNA, [S. l.], v. 86, n. 208, p. 271–280, 2019. DOI: 10.15446/dyna.v86n208.76105. Disponível em: https://revistas.unal.edu.co/index.php/dyna/article/view/76105. Acesso em: 25 mar. 2026.

Chicago

Bastos, Fernando Zelak Leite, Cassius Tadeu Scarpin, y Jose Eduardo Pécora Junior. 2019. «Picking planning and quality control analysis using discrete simulation: case in a food industry». DYNA 86 (208):271-80. https://doi.org/10.15446/dyna.v86n208.76105.

Harvard

Bastos, F. Z. L., Scarpin, C. T. y Pécora Junior, J. E. (2019) «Picking planning and quality control analysis using discrete simulation: case in a food industry», DYNA, 86(208), pp. 271–280. doi: 10.15446/dyna.v86n208.76105.

MLA

Bastos, F. Z. L., C. T. Scarpin, y J. E. Pécora Junior. «Picking planning and quality control analysis using discrete simulation: case in a food industry». DYNA, vol. 86, n.º 208, enero de 2019, pp. 271-80, doi:10.15446/dyna.v86n208.76105.

Turabian

Bastos, Fernando Zelak Leite, Cassius Tadeu Scarpin, y Jose Eduardo Pécora Junior. «Picking planning and quality control analysis using discrete simulation: case in a food industry». DYNA 86, no. 208 (enero 1, 2019): 271–280. Accedido marzo 25, 2026. https://revistas.unal.edu.co/index.php/dyna/article/view/76105.

Vancouver

1.
Bastos FZL, Scarpin CT, Pécora Junior JE. Picking planning and quality control analysis using discrete simulation: case in a food industry. DYNA [Internet]. 1 de enero de 2019 [citado 25 de marzo de 2026];86(208):271-80. Disponible en: https://revistas.unal.edu.co/index.php/dyna/article/view/76105

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CrossRef citations2

1. Maria Pia Garcia-Davila, Favianna Mariel Mendoza-Gallo, Juan Carlos Quiroz-Flores. (2026). Optimizing recycling efficiency in the PET plastic sector through BPM, quality control sampling and circular economy framework: A case study in Peru. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON MATHEMATICS, ENGINEERING AND INDUSTRIAL APPLICATIONS: ICoMEIA2024. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON MATHEMATICS, ENGINEERING AND INDUSTRIAL APPLICATIONS: ICoMEIA2024. 3462, p.030001. https://doi.org/10.1063/5.0308465.

2. Eleonora Bottani, Letizia Tebaldi, Giorgia Casella, Cristina Mora. (2025). Key Performance Indicators for Food Supply Chain: A Bibliometric and Systematic Literature Review. Applied Sciences, 15(7), p.3841. https://doi.org/10.3390/app15073841.

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