Bibliographic citations
Chavez, A., Pariona, M. (2024). Propuesta para aumentar la productividad en la línea de producción de Extractor de aire utilizando las herramientas Heijunka, MRP, Estudio de Tiempos y Movimientos y 5S en una empresa del sector metalmecánico [Trabajo de Suficiencia Profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/682828
Chavez, A., Pariona, M. Propuesta para aumentar la productividad en la línea de producción de Extractor de aire utilizando las herramientas Heijunka, MRP, Estudio de Tiempos y Movimientos y 5S en una empresa del sector metalmecánico [Trabajo de Suficiencia Profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/682828
@misc{renati/1299928,
title = "Propuesta para aumentar la productividad en la línea de producción de Extractor de aire utilizando las herramientas Heijunka, MRP, Estudio de Tiempos y Movimientos y 5S en una empresa del sector metalmecánico",
author = "Pariona Nuñez, Miguel Angel",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
The main objective of this study is the application of Lean Manufacturing tools to increase productivity in the production line of air extractors in a metal-mechanical company. During the development, it starts with the problem of the study, collection of research background and diagnosis of the current situation in the production of air extractors. Then, we proceed with the methodology of the study, considering a quantitative approach, applicative level, pre-experimental design and deductive method. Next, we have the measurement control indicators to evaluate the proposal proposed from the current and improved scenario in order to interpret the results in its development. As a result, it was possible to apply the lean manufacturing tools (MRP, Heijunka, 5 S, Time and Motion Studies) having a cost reduction from S/. 34,535.00 to S/. 15,750.00 per year, increase in productivity from 0.301 und/hh to 0.825 und/hh; increase in production from 33 units to 66 units per month; also, efficiency improved from 81.20% to 87.55% and an optimization of production time from 31.1 hours to 13.8 hours. It was also validated with the simulation using the ProModel program.
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