Application of statistical methods with exponential smoothing double and triple for demand forecasting in the inventory management
The statistical methods with double and triple exponential smoothing widely used to model significant trends in non-stationary time series data are applied in this work to obtain short-term forecasts for the planning of the demand of the productive process in a metallurgical industry of the north of...
| Authors: | , , , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2019 |
| Country: | Brasil |
| Institution: | Associação Brasileira de Engenharia de Produção (ABEPRO) |
| Repository: | Revista Produção Online |
| Language: | Portuguese |
| OAI Identifier: | oai:ojs.www.producaoonline.org.br:article/3539 |
| Online Access: | https://www.producaoonline.org.br/rpo/article/view/3539 |
| Access Level: | Open access |
| Keyword: | Statistical methods. Exponential smoothing. Forecasting. Inventory management. Métodos estatísticos. Suavização exponencial. Previsão. Gestão de estoques. |
| Summary: | The statistical methods with double and triple exponential smoothing widely used to model significant trends in non-stationary time series data are applied in this work to obtain short-term forecasts for the planning of the demand of the productive process in a metallurgical industry of the north of Santa Catarina. The main objective of the application of such methods is to establish demand forecasting in order to anticipate future sales scenarios in two categories of products and obtain the best utilization of productive capacity through adequate inventory management to reduce risks in the process decision-making in this industry. The results obtained with the appropriate selection of the predictive methods with exponential smoothing, object of study of this work, were fundamental for the analyst of the system of forecast of demand to direct special attention to the degree of accuracy that integrated to an efficient inventory management policy was responsible per minimizing the effects of variability and operational costs, as well as contribute to the improvement of service levels and the consequent increase in the profitability of the industry involved. |
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