Bibliographic citations
Centeno, A., Osorio, D. (2020). Modelo de gestión de inventario basado en Lean Warehousing y DDMRP para maximizar los pedidos perfectos - caso de una empresa vitivinícola [Trabajo de investigación, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/654630
Centeno, A., Osorio, D. Modelo de gestión de inventario basado en Lean Warehousing y DDMRP para maximizar los pedidos perfectos - caso de una empresa vitivinícola [Trabajo de investigación]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2020. http://hdl.handle.net/10757/654630
@misc{renati/393695,
title = "Modelo de gestión de inventario basado en Lean Warehousing y DDMRP para maximizar los pedidos perfectos - caso de una empresa vitivinícola",
author = "Osorio Barra, David Edward",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2020"
}
The perfect order rate is a superior metric that measures the quality and performance of warehouse management. This indicator presents 4 components, which are the delivery on time, complete, without damage and with all the perfect documentation of the orders. These factors are related to the profitability of organizations. The objective of this study is to propose a warehouse management model based on Lean Warehousing and the Demand Driven Material Requirements Planning (DDMRP) methodology to maximize the rate of fulfillment of perfect orders in warehouses in the wine sector. Therefore, warehouse-centric practices such as ABC analysis, 5S and DDMRP methodology are developed, with an emphasis on picking errors and stock outs. Similarly, the DMAIC methodology is used as the basis for the application of the tools of the Lean Warehousing model. A case study was used with a perfect order value of 47.2%, which represented a technical gap of 30% with respect to the market. Thus, the validation was carried out using the discrete event simulation method for inventories with reorder point. Arena simulation software, full version 14.5, was used with a 95% confidence level. In the results, the indicator of perfect orders increased to 82.6%, representing an improvement of 35.4% from the current situation. Likewise, stock breakages and picking errors were reduced by 18.2% and 23.6%, respectively.
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