TY - GEN
T1 - Integrated Lean Logistics - Warehousing model to reduce Lead Time in an SME of food sector: A research in Peru
AU - Quiroz-Flores, Juan Carlos
AU - Canales-Huaman, Daniela Steisy
AU - Gamio-Valdivia, Karina Guiuliana
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/1/12
Y1 - 2022/1/12
N2 - The food industry represented 2019 3.2% of the Gross Domestic Product (GDP) in Peru, in addition to presenting high employability being that the sector contained 7.4% of the Economically Active Population (EAP) [1]. However, due to the world crisis caused by COVID 19, this sector has been harmed in the year 2020 because the GDP of the accommodation and restaurants sector decreased by 50.2% compared to the previous year [2]. For that reason, strengthening this industry is considered crucial. One of the most critical links in the management of the supply chain of material, this problem results in the late delivery of orders to their customers, which would generate significant monetary losses and a bad reputation. In this sense, the present research proposes an integral improvement model based on the combination of tools such as the 5S ordering of raw material under a multi-criteria ABC approach, FEFO, MRP, Forecasting, and BPM, whose objective is to reduce the lead time. The model was validated through a simulation in Arena 16.1, where a reduction in delivery time and the frequency of extra purchases in 7.2% y 50%.
AB - The food industry represented 2019 3.2% of the Gross Domestic Product (GDP) in Peru, in addition to presenting high employability being that the sector contained 7.4% of the Economically Active Population (EAP) [1]. However, due to the world crisis caused by COVID 19, this sector has been harmed in the year 2020 because the GDP of the accommodation and restaurants sector decreased by 50.2% compared to the previous year [2]. For that reason, strengthening this industry is considered crucial. One of the most critical links in the management of the supply chain of material, this problem results in the late delivery of orders to their customers, which would generate significant monetary losses and a bad reputation. In this sense, the present research proposes an integral improvement model based on the combination of tools such as the 5S ordering of raw material under a multi-criteria ABC approach, FEFO, MRP, Forecasting, and BPM, whose objective is to reduce the lead time. The model was validated through a simulation in Arena 16.1, where a reduction in delivery time and the frequency of extra purchases in 7.2% y 50%.
UR - https://hdl.handle.net/20.500.12724/17617
UR - https://www.scopus.com/pages/publications/85132025650
UR - https://www.mendeley.com/catalogue/420fb4a7-c061-3345-b971-22ff495dadcf/
U2 - 10.1145/3524338.3524366
DO - 10.1145/3524338.3524366
M3 - Articulo (Contribución a conferencia)
AN - SCOPUS:85132025650
T3 - ACM International Conference Proceeding Series
SP - 182
EP - 188
BT - IEIM 2022 - 2022 3rd International Conference on Industrial Engineering and Industrial Management
PB - Association for Computing Machinery
T2 - 3rd International Conference on Industrial Engineering and Industrial Management, IEIM 2022
Y2 - 12 January 2022 through 14 January 2022
ER -