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

doi:10.1109/CONIITI57704.2022.9953633

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 conferencia › revisión exhaustiva

6 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 original	Inglés estadounidense
Título de la publicación alojada	2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings
Editores	Victor Manuel Fontalvo Morales
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781665465250
DOI	https://doi.org/10.1109/CONIITI57704.2022.9953633
Estado	Indizado - 2022
Publicado de forma externa	Sí
Evento	2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Bogota, Colombia Duración: 5 oct. 2022 → 7 oct. 2022

Serie de la publicación

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

Conferencia

Conferencia	2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022
País/Territorio	Colombia
Ciudad	Bogota
Período	5/10/22 → 7/10/22

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Publisher Copyright:
© 2022 IEEE.

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10.1109/CONIITI57704.2022.9953633

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Garcia-Chavez, G. I., Del Rosario Carmelo-Mendieta, V., Collao-Diaz, M. F., & Quiroz-Flores, J. C. (2022). Inventory management model based on Demand Forecasting, 5S, BPM and Max-Min to improve turnover in commercial enterprises. En V. M. F. Morales (Ed.), 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings (2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONIITI57704.2022.9953633

Garcia-Chavez, Gloria Isabel ; Del Rosario Carmelo-Mendieta, Vanessa ; Collao-Diaz, Martin Fidel et al. / Inventory management model based on Demand Forecasting, 5S, BPM and Max-Min to improve turnover in commercial enterprises. 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings. editor / Victor Manuel Fontalvo Morales. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings).

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

abstract = "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.",

keywords = "5S, BPM, Inventory Turnover, Max-Min inventory, commercial enterprise, demand forecast",

author = "Garcia-Chavez, {Gloria Isabel} and {Del Rosario Carmelo-Mendieta}, Vanessa and Collao-Diaz, {Martin Fidel} and Quiroz-Flores, {Juan Carlos}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 ; Conference date: 05-10-2022 Through 07-10-2022",

year = "2022",

doi = "10.1109/CONIITI57704.2022.9953633",

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series = "2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Garcia-Chavez, GI, Del Rosario Carmelo-Mendieta, V, Collao-Diaz, MF & Quiroz-Flores, JC 2022, Inventory management model based on Demand Forecasting, 5S, BPM and Max-Min to improve turnover in commercial enterprises. En VMF Morales (ed.), 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings. 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022, Bogota, Colombia, 5/10/22. https://doi.org/10.1109/CONIITI57704.2022.9953633

Inventory management model based on Demand Forecasting, 5S, BPM and Max-Min to improve turnover in commercial enterprises. / Garcia-Chavez, Gloria Isabel; Del Rosario Carmelo-Mendieta, Vanessa; Collao-Diaz, Martin Fidel et al.
2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings. ed. / Victor Manuel Fontalvo Morales. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings).

Producción científica: Libro o Capítulo del libro › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Inventory management model based on Demand Forecasting, 5S, BPM and Max-Min to improve turnover in commercial enterprises

AU - Garcia-Chavez, Gloria Isabel

AU - Del Rosario Carmelo-Mendieta, Vanessa

AU - Collao-Diaz, Martin Fidel

AU - Quiroz-Flores, Juan Carlos

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

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KW - BPM

KW - Inventory Turnover

KW - Max-Min inventory

KW - commercial enterprise

KW - demand forecast

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U2 - 10.1109/CONIITI57704.2022.9953633

DO - 10.1109/CONIITI57704.2022.9953633

M3 - Conference contribution

AN - SCOPUS:85143705234

T3 - 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings

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

A2 - Morales, Victor Manuel Fontalvo

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022

Y2 - 5 October 2022 through 7 October 2022

ER -

Garcia-Chavez GI, Del Rosario Carmelo-Mendieta V, Collao-Diaz MF, Quiroz-Flores JC. Inventory management model based on Demand Forecasting, 5S, BPM and Max-Min to improve turnover in commercial enterprises. En Morales VMF, editor, 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2022. (2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings). doi: 10.1109/CONIITI57704.2022.9953633

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

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