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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Detalles Bibliográficos
Autor: Casanova González, Franco David
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
Descripción
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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