Service model based on lean tools to improve order fulfillment rate in a SMEs in the commercial sector

Descripción del Articulo

The commercial sector has been growing steadily in recent years. However, there are problems within logistics that are detrimental to customer satisfaction; the objective of companies is to deliver orders on time and avoid large losses. That said, in the present research, the problem that generates...

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Detalles Bibliográficos
Autores: Quiroz Flores, Juan Carlos, Caso Vicente, Katterin Jennyfer, Galarreta Bellido, Marina Elvira
Formato: objeto de conferencia
Fecha de Publicación:2023
Institución:Universidad de Lima
Repositorio:ULIMA-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.ulima.edu.pe:20.500.12724/19451
Enlace del recurso:https://hdl.handle.net/20.500.12724/19451
https://dx.doi.org/10.18687/LACCEI2023.1.1.113
Nivel de acceso:acceso abierto
Materia:Servicio al cliente
Pequeñas y medianas empresas
Logística empresarial
Customer services
Business logistics
Small and medium-sized enterprises
https://purl.org/pe-repo/ocde/ford#2.11.04
Descripción
Sumario:The commercial sector has been growing steadily in recent years. However, there are problems within logistics that are detrimental to customer satisfaction; the objective of companies is to deliver orders on time and avoid large losses. That said, in the present research, the problem that generates the greatest economic losses for the company is the high percentage of unfulfilled orders. The objective is to reduce the technical gap of unfulfilled orders by implementing a model based on the Lean methodology, through the application of 5S, ABC and Kanban; achieving the improvement of the objectives of the proposed indicators. The research focuses on a warehouse where the root causes of the problem are identified and quantified, to subsequently attack them through Lean tools. Finally, through the use of Arena software simulation, it was demonstrated that the proposed model achieves a reduction of 38.8%, 12.32% and 47.23% in picking times, registration to the system and total simulation time, respectively, thus improving the fulfillment of deliveries to the customer until reaching the target of 5%.
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