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.
| Original language | American English |
|---|---|
| Title of host publication | 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings |
| Editors | Victor Manuel Fontalvo Morales |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781665465250 |
| DOIs | |
| State | Indexed - 2022 |
| Externally published | Yes |
| Event | 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Bogota, Colombia Duration: 5 Oct 2022 → 7 Oct 2022 |
Publication series
| Name | 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 - Conference Proceedings |
|---|
Conference
| Conference | 2022 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2022 |
|---|---|
| Country/Territory | Colombia |
| City | Bogota |
| Period | 5/10/22 → 7/10/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- 5S
- BPM
- Inventory Turnover
- Max-Min inventory
- commercial enterprise
- demand forecast
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