EOQ Inventory Model in a Metalworking MSE with Intermittent Demand: A Case Study

Jaime Abel Jiménez Ayhuasi, José Antonio Taquía Gutiérrez

Producción científica: Capítulo del libro/informe/acta de congresoCapítulorevisión exhaustiva

Resumen

The main objective of this research article is to optimize costs and logistic KPIs applying an economic order quantity (EOQ) inventory model in a metal-mechanic MSE with intermittent demand. Firstly, the forecast model with the lowest MAD and ECM is selected. The object under study, after ABC classification, belongs to the family of products located in class A due to its valuation and participation in the inventory. The Croston method is considered the most effective forecast model. Secondly, an aggregate planning is developed to satisfy the projection. Then, the EOQ or Wilson model is implemented to reduce inventory costs. Finally, to validate the calculated data, a simulation model is built in Arena with 50 replications. As a result, the inventory costs were reduced to 22.6%
Idioma originalInglés estadounidense
Título de la publicación alojadaEOQ Inventory Model in a Metalworking MSE with Intermittent Demand: A Case Study
EditoresLoon-Ching Tang
Lugar de publicaciónThe Netherlands
EditorialIOS Press
Páginas128 - 139
Número de páginas11
Volumen35
ISBN (versión digital)978-1-64368-409-3
ISBN (versión impresa)978-1-64368-408-6
DOI
EstadoPublicada - 27 jul. 2023
Evento10th International Conference on Industrial Engineering and Applications- Asia - Phuket, Tailandia
Duración: 4 abr. 20236 abr. 2023
Número de conferencia: 10
http://www.iciea.org/

Serie de la publicación

NombreAdvances in Transdisciplinary Engineering
EditorialIOS Press
Volumen35
ISSN (versión impresa)2352-751X
ISSN (versión digital)2352-7528

Conferencia

Conferencia10th International Conference on Industrial Engineering and Applications- Asia
Título abreviadoICIEA-ASIA
País/TerritorioTailandia
CiudadPhuket
Período4/04/236/04/23
Dirección de internet

Palabras Clave

  • Intermittent demand forecasting
  • Croston Method
  • EOQ Model
  • Logistic indicators
  • simulación computacional

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