Inventory management model based on Demand Forecasting, 5S, BPM and Max-Min to improve turnover in commercial enterprises

Gloria Isabel Garcia-Chavez, Vanessa Del Rosario Carmelo-Mendieta, Martin Fidel Collao-Diaz, Juan Carlos Quiroz-Flores

Producción científica: Libro o Capítulo del libro Contribución a la conferenciarevisión exhaustiva

4 Citas (Scopus)

Resumen

The commercial sector in Peru has been developing progressively over the years, projecting an average growth of 4.4% per year for the period 2022-2024. For this reason, commercial companies must be more prepared than ever to satisfy the requirements of the demand, being important to analyze one of the main problems of the sector, which include the inventory turnover. In this sense, it is crucial to identify the causes that generate the problem, such as inadequate management in the purchasing and warehouse processes. This research develops an inventory management model based on the combination of four tools (demand forecast, 5S, BPM and Max-Min policy) that aims to improve turnover in commercial enterprises. The results demonstrated the effectiveness of the model by significantly increasing the rotation of the Explorer 115 C/C and R3 Evo 110 agricultural tractor by 39% and 49% respectively.

Idioma originalInglés estadounidense
Título de la publicación alojada2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings
EditoresVictor Manuel Fontalvo Morales
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665465250
DOI
EstadoIndizado - 2022
Publicado de forma externa
Evento2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Bogota, Colombia
Duración: 5 oct. 20227 oct. 2022

Serie de la publicación

Nombre2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings

Conferencia

Conferencia2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022
País/TerritorioColombia
CiudadBogota
Período5/10/227/10/22

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Publisher Copyright:
© 2022 IEEE.

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