Quantitative Estimation of Demand for Conveyor Belt Supplies
No hay miniatura disponible
Fecha
2022
Profesor/a Guía
Facultad/escuela
Idioma
en
Título de la revista
ISSN de la revista
Título del volumen
Editor
Elsevier
Nombre de Curso
Licencia CC
Attribution-NonCommercial-NoDerivatives 4.0 International
Licencia CC
Resumen
Demand forecasts provides quantitative data to estimate, with a reasonable degree of certainty, customers’ requirements of a company. Applying this tool in manufacturing companies allows them to generate predictions for decision making. Forecasts have a transverse impact on finances, human resources, inventories, and production, among others. In Chile, qualitative models are used to make these estimates based on information from the sales force, customers, or group of experts. This article incorporates three exponential smoothing models into these estimates. Data is available from a manufacturing company (2016 to 2019); it is used to make comparisons and adjustments to select, the best model for each product. Also, a correlation and covariance analysis is carried out between the inputs, to determine the degree of relationship between the products and thus project their demand.
Notas
TEXTO COMPLETO EN INGLÉS
Palabras clave
Forecast, Demand, Time Series, Exponential Smoothing, Correlation, Covariance
Citación
Procedia Computer Science, Volume 203 , 2022, Pages 605-609
DOI
https://doi.org/10.1016/j.procs.2022.07.087