Quantitative Estimation of Demand for Conveyor Belt Supplies

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dc.contributor.authorNuñez-Uribe, C.
dc.contributor.authorOlmedo, A.
dc.contributor.authorRíos, J.
dc.contributor.authorCoronado-Hernández, J.
dc.contributor.authorMorillo, D.
dc.contributor.authorGatica, G.
dc.contributor.authorUmaña-Ibáñez, S.
dc.contributor.authorCabrera, G.
dc.date.accessioned2024-09-10T16:02:09Z
dc.date.available2024-09-10T16:02:09Z
dc.date.issued2022
dc.descriptionTEXTO COMPLETO EN INGLÉS
dc.description.abstractDemand 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.
dc.description.urihttps://www-sciencedirect-com.recursosbiblioteca.unab.cl/science/article/pii/S1877050922006925
dc.identifier.citationProcedia Computer Science, Volume 203 , 2022, Pages 605-609
dc.identifier.doihttps://doi.org/10.1016/j.procs.2022.07.087
dc.identifier.issn1877-0509
dc.identifier.urihttps://repositorio.unab.cl/handle/ria/60022
dc.language.isoen
dc.publisherElsevier
dc.rights.licenseAttribution-NonCommercial-NoDerivatives 4.0 International
dc.subjectForecast
dc.subjectDemand
dc.subjectTime Series
dc.subjectExponential Smoothing
dc.subjectCorrelation
dc.subjectCovariance
dc.titleQuantitative Estimation of Demand for Conveyor Belt Supplies
dc.typeArtículo
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