Vol. 11 Núm. 1 (2020): Revista Aglala
Artículos Cientificos

Formación de celdas de manufacturas dinámicas para la toma de decisiones en el diseño de instalaciones industriales: una revisión

Laura Y. Escobar Rodríguez
Universidad Industrial de Santander
Edwin A. Garavito Hernández
Universidad Industrial de Santander
Leonardo H. Talero Sarmiento
Universidad Industrial de Santander
Publicado June 3, 2020
Palabras clave
  • Celdas de manufactura dinámicas,
  • planeación y diseño de instalaciones,
  • problema de formación de celdas de manufactura,
  • corporativo
Cómo citar
[1]
Escobar Rodríguez, L.Y., Garavito Hernández, E.A. y Talero Sarmiento, L.H. 2020. Formación de celdas de manufacturas dinámicas para la toma de decisiones en el diseño de instalaciones industriales: una revisión. Aglala. 11, 1 (jun. 2020), 169-184.

Resumen

Este artículo presenta una revisión de literatura con el fin de caracterizar el Problema de Formación de Celdas de Manufactura Dinámicas, realizando la identificación de los criterios de optimización, las principales restricciones consideradas y los métodos de solución más usados. Para ello, se condujo una adaptación de la declaración PRISMA para revisiones sistemáticas, en conjunto con una metodología bola de nieve para la selección de los estudios a analizar; la búsqueda de documentos se realiza en las bases de datos Web of Science y Scopus, considerando una ventana de tiempo entre 2007 y 2019. Como resultados generales, se encuentra que la minimización de costos es el criterio de optimización utilizado con mayor frecuencia y que las restricciones usualmente consideradas están asociadas a la secuencia de operaciones, averías de máquinas, y variación del tamaño de lote de procesamiento. De otra parte, considerando la naturaleza altamente combinatoria de los problemas de optimización revisados, se encuentra que los métodos de solución metaheurísticos utilizados en mayor medida son algoritmos genéticos, y recocido simulado. Finalmente, se determinan tres tendencias de investigación primero, la incorporación de dos o más criterios de optimización en una formulación matemática; segundo, el desarrollo e implementación de algoritmos metaheurísticos híbridos y; tercero, la evaluación de los métodos de solución existentes a partir de problemas de referencia o aplicaciones industriales reales.

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