Sistema de predicción de kilometraje y servicios automotrices
Descripción del Articulo
Currently in Peru, many dealerships or automotive workshops do not have ERP systems or systems that make predictions about the services they provide, generating a decrease in revenue due to loss of customers and lack or overstock of spare parts. Due to this problem, the research and development of a...
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Formato: | tesis de grado |
Fecha de Publicación: | 2022 |
Institución: | Universidad de Lima |
Repositorio: | ULIMA-Institucional |
Lenguaje: | español |
OAI Identifier: | oai:repositorio.ulima.edu.pe:20.500.12724/17404 |
Enlace del recurso: | https://hdl.handle.net/20.500.12724/17404 |
Nivel de acceso: | acceso abierto |
Materia: | Sistemas de información en administración Sistemas de apoyo a las decisiones Innovaciones tecnológicas Talleres de reparación de automóviles Management information systems Decision support systems Technological innovations Automobile repair shops https://purl.org/pe-repo/ocde/ford#2.02.04 |
Sumario: | Currently in Peru, many dealerships or automotive workshops do not have ERP systems or systems that make predictions about the services they provide, generating a decrease in revenue due to loss of customers and lack or overstock of spare parts. Due to this problem, the research and development of a predictive system for future vehicle maintenance services, resource utilization and customer analysis was carried out, which will increase the profitability and quality of service of automotive dealerships and workshops. In this first minimum viable product, a desktop software was developed through which customers can enter their database of maintenance services performed in Excel format, then they can add new data and update the process in which the service is, and can also export this updated database. Finally, the added value of this minimum viable product will be the prediction of maintenance services according to vehicle, vehicle model, resource utilization prediction and customer analysis, all this information will be displayed with their accuracy percentages. Concluding with the tests performed for the predictions of maintenance services excluding outliers, 63% of the predictions had an error between -2000 and 2000 kilometers, and 47% of the predictions had an error between -1000 and 1000 kilometers. |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).