The optimization of production processes in the clothing industry using the simulation of discrete events

Descripción del Articulo

It is important for small growing textile companies to make key decisions based on accurate and reliable information about the present production process and how future changes could affect them. Using traditional mathematical methods it is not possible to accurately and reliably reflect the real st...

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Detalles Bibliográficos
Autores: Aragón Guía, Luis Alfredo, Díaz Callo, Yordi Jesús, Juarez Flores, Marilyn Fabiola
Formato: artículo
Fecha de Publicación:2020
Institución:Universidad La Salle
Repositorio:Revistas - Universidad La Salle
Lenguaje:español
OAI Identifier:oai:ojs.revistas.ulasalle.edu.pe:article/9
Enlace del recurso:https://revistas.ulasalle.edu.pe/innosoft/article/view/9
https://doi.org/10.48168/innosoft.s1.a9
https://purl.org/42411/s1/a9
https://n2t.net/ark:/42411/s1/a9
Nivel de acceso:acceso abierto
Materia:Discrete events
Simulation
Textile
Simulación
Textil
Eventos discretos
Descripción
Sumario:It is important for small growing textile companies to make key decisions based on accurate and reliable information about the present production process and how future changes could affect them. Using traditional mathematical methods it is not possible to accurately and reliably reflect the real stochastic behaviour of processes and activities carried out in this industry. There are, however, information technologies such as the computer simulation technique that allow such information to be obtained taking this behaviour into account.he research carried out a simulation study of the garment making process of a small textile company in order to propose a better distribution of resources by experimenting with a simulation model of the process, In addition, some of the quantitative information obtained with this technique is presented. The results obtained show that making changes in assigning tasks and resources reduces the production time of a batch of 100 units in one hour and reduces approximately 30 minutes the average time that a unit remains in the system. All the information was obtained by means of a simulation model verified and validated without the need to experience such changes with the real system.
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