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Please use this identifier to cite or link to this item:
https://repositorio.utn.edu.ec/handle/123456789/19590Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | González Garzón, Cristina | - |
| dc.contributor.author | Montero Santos, Yakcleem | - |
| dc.contributor.author | Saraguro Piarpuezan, Ramiro V. | - |
| dc.date.accessioned | 2026-04-14T17:23:42Z | - |
| dc.date.available | 2026-04-14T17:23:42Z | - |
| dc.date.created | 2021-08-02 | - |
| dc.date.issued | 2026-04-14 | - |
| dc.identifier.issn | 2169-8767 | - |
| dc.identifier.uri | https://repositorio.utn.edu.ec/handle/123456789/19590 | - |
| dc.description.abstract | La adecuada gestión de los inventarios dentro de cualquier empresa es importante porque representan un activo con una inversión considerable, y una mala gestión genera desperdicios. Dentro de los tipos de inventarios se encuentran las materias primas, las cuales requieren un mayor control, ya que de su correcta planificación dependen las actividades posteriores de la cadena de suministro. Al realizar un diagnóstico situacional en la empresa objeto de estudio, se determinó que existían pérdidas económicas debido a la obsolescencia del inventario en el almacén, retrasos en las entregas que ocasionaban multas y reclamos, lo que evidenció la necesidad de aplicar un modelo de inventario que permita reducir costos y cumplir con los plazos de entrega. Se inicia clasificando los inventarios según su nivel de importancia con respecto al nivel de ventas, con el fin de determinar cuáles son los más demandados por los clientes. Se analiza la dispersión de los datos para conformar la base de datos y detectar valores atípicos. El pronóstico de la demanda se realizó con el Statistical Package for the Social Sciences (SPSS) y R versión 3.6.2, específicamente con el paquete nnfor para redes neuronales. Para la planificación de las unidades de mantenimiento de inventario (SKU) se utilizan los modelos Silver-Meal (SM), Wagner-Whitin (WW) y Balance de Período Fragmentado (BFP), obteniendo un resultado óptimo con una reducción del 57,89%, en comparación con el valor de realizar un pedido mensual durante el período. | es_EC |
| dc.language.iso | spa | es_EC |
| dc.publisher | Conference on Industrial Engineering and Operations Management | es_EC |
| dc.rights | openAccess | es_EC |
| dc.rights | Atribución-NoComercial-CompartirIgual 3.0 Ecuador | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/ec/ | * |
| dc.subject | GESTIÓN | es_EC |
| dc.subject | INVENTARIO | es_EC |
| dc.subject | INVERSIÓN | es_EC |
| dc.subject | PLANIFICACIÓN | es_EC |
| dc.title | Modelo de inventario para materia prima: un estudio de caso de una empresa química | es_EC |
| dc.type | Article | es_EC |
| dc.description.degree | N/A | es_EC |
| dc.coverage | Ibarra. Ecuador | es_EC |
| dc.contributor.orcid | https://orcid.org/0000-0003-0019-2033 | es_EC |
| dc.contributor.orcid | https://orcid.org/0000-0002-0010-8201 | es_EC |
| dc.contributor.orcid | https://orcid.org/0000-0002-6244-5246 | es_EC |
| dc.title.en | Inventory model for raw material: A case study of a chemical company | es_EC |
| dc.subject.en | MANAGEMENT | es_EC |
| dc.subject.en | INVENTORY | es_EC |
| dc.subject.en | INVESTMENT | es_EC |
| dc.subject.en | PLANNING | es_EC |
| dc.description.abstract-en | Proper management of inventories within any company is important because they represent an asset with considerable investment and mishandling generates waste. Within the types of inventories, there are raw materials takes, which require greater control, since their proper planning depends on the subsequent activities of the supply chain. By making a situational diagnosis at the company under study it was determined that there were economic losses due to inventory obsolescence in the warehouse, delays in deliveries which led to fines and claims, demonstrating the need to apply an inventory model that allows to reduce its costs and meet delivery deadlines. It starts by classifying inventories according to their level of importance with respect to the level of sales, in order to determine which of them are the most demanded by customers. The dispersion of the data is analyzed to form the database and look for outliers. The demand forecast was made with the Statistical Package for the Social Sciences (SPSS) and R Version 3.6.2, specifically with the package nnfor for neural networks. For the planning of the stock keeping unit (SKU) it is done with the models Silver Meal (SM), Wagner Whitin (WW) Fragmented Period Balance (BFP); determining an optimal result with a reduction of 57,89%, compared to the value of placing a monthly order during the period. | es_EC |
| dc.identifier.doi | http://ieomsociety.org/proceedings/2021rome/158.pdf | es_EC |
| Appears in Collections: | Artículos | |
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