Citas bibligráficas
Felix, A., Casas, J. (2024). Mejora del nivel de servicio en una empresa distribuidora de luminarias en Perú mediante la aplicación de Slotting, Standard Work y Forecast [Trabajo de Suficiencia Profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/683013
Felix, A., Casas, J. Mejora del nivel de servicio en una empresa distribuidora de luminarias en Perú mediante la aplicación de Slotting, Standard Work y Forecast [Trabajo de Suficiencia Profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/683013
@misc{renati/1032653,
title = "Mejora del nivel de servicio en una empresa distribuidora de luminarias en Perú mediante la aplicación de Slotting, Standard Work y Forecast",
author = "Casas Soto, José Hernán",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
The lighting sector in Peru reached a valuation of USD 75 million in 2022 and with a projected growth of 6.2% per year until 2030; such growth is encouraged by the demand for its products in the construction and commerce sectors; which, together, contribute significantly to the country's economy. However, this sector faces crucial challenges in relation to the complete and timely delivery of its products, which are quantified through the OTIF (On Time In Full) indicator; which is determinant to evaluate the level of service within the supply chain of the lighting sector. Having mentioned the above, for the present research, multiple tools have been implemented such as Slotting to optimize the flow of materials and organize the location of SKU's, in order to minimize un necessary movements within the warehouse; Standardized work to standardize manual activities within the warehouse; and demand forecast, holt-winter, which allowed smoothing and adjusting demand projections in the long term. The synergy between these tools was evidenced in the significant increase in the company's service level. The main results obtained from the pilot test, implemented in the case study company, were a reduction of the picking rework rate to 2% of the order quantity indicator with picking errors to 2% and of the demand forecast error indicator to 1%; this contributing to the increase of the central indicator (OTIF) to 90.12%.
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