Bibliographic citations
Caceres, D., Avila, R. (2024). Mejora en el proceso de almacenamiento basada en EOQ, ABC y pronósticos para incrementar el índice de rotación de inventarios en una pyme comercial de productos ferreteros [Trabajo de Suficiencia Profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/683671
Caceres, D., Avila, R. Mejora en el proceso de almacenamiento basada en EOQ, ABC y pronósticos para incrementar el índice de rotación de inventarios en una pyme comercial de productos ferreteros [Trabajo de Suficiencia Profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/683671
@misc{renati/1300709,
title = "Mejora en el proceso de almacenamiento basada en EOQ, ABC y pronósticos para incrementar el índice de rotación de inventarios en una pyme comercial de productos ferreteros",
author = "Avila Nolasco, Rocio Lizet",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
Micro, small, and medium-sized enterprises (MSMEs) represent 99.5% of formal businesses in Latin America, with the construction sector—where many hardware businesses are found—experiencing accelerated growth. However, an exhaustive review of the literature and sectoral studies indicates that these enterprises face a significant risk of failure in the short term due to various issues, with poor warehouse management standing out, which leads to a low inventory turnover rate. In this context, this Applied Research Project focuses on implementing an improvement in the storage process of a company dedicated to the commercialization of hardware products in the city of Lima, with the objective of increasing the turnover rate of its stored products. The methodology employed is based on the application of the Economic Order Quantity (EOQ) model, demand forecasting, and ABC classification. The main contribution of this research lies in optimizing demand estimation accuracy, which will enable a more adequate purchasing strategy and inventory classification according to importance and type of material, thereby minimizing product loss and preventing future damage.
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