Análise da aplicação de modelos de previsão de demanda: estudo de caso aplicado à venda dos produtos de uma malharia na cidade de Abaetetuba-PA
It is not new that there is rivalry between organizations of different sectors of the world economy, and an excellent administration of production of goods and services becomes this sense, the fundamental key to many businesses can survive or even get to success within this economic scenario. This p...
| Autor principal: | CASTRO JÚNIOR, Jamirês Marques |
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| Grau: | Trabalho de Conclusão de Curso - Graduação |
| Idioma: | por |
| Publicado em: |
2022
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| Assuntos: | |
| Acesso em linha: |
https://bdm.ufpa.br:8443/jspui/handle/prefix/4415 |
| Resumo: |
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It is not new that there is rivalry between organizations of different sectors of the world economy, and an excellent administration of production of goods and services becomes this sense, the fundamental key to many businesses can survive or even get to success within this economic scenario. This paper analyzed some specific points in the Planning and Production Control of a micro-enterprise segment of the clothing in the clothing industry, seeking appropriate methods for major problems the company was facing related to demand forecasting. Predictions are of paramount importance for the development of strategic planning in all its dimensions and this work has as main objective to propose a model to forecast demand for the company Mariarte Industry and Commerce Ltda Clothes that can effectively manage the sale of products, based on the literature of management of Production and concepts related to the manufacturing technology. This study was conducted in a garment manufacturing company, located in Abaetetuba which is approximately 110 km from the state capital. For the analysis of adherence research visits were made to the company and interviews with the owner of the property who assisted in data collection. At the end of the study evaluated the adequacy of two models that showed the lowest margins of error that was the method of moving average and exponential smoothing model with trend and seasonality. |