Comparativo de métodos de pronóstico en series de tiempo para la demanda de repuestos automotrices
DOI:
https://doi.org/10.33064/iycuaa2025945451Palabras clave:
pronóstico de la demanda, mercado de autopartes, patrones de demanda, cadena de suministro, series de tiempoResumen
La inevitable necesidad que las empresas del sector de repuestos automotrices tienen de pronosticar sus niveles de producción es la base del desarrollo de este trabajo. Este artículo muestra el análisis probabilístico de la demanda de tres empresas de autopartes mexicanas enfocadas a la producción y venta nacional e internacional. Se analizaron 312 series de tiempo basadas en el histórico mensual de demanda, aplicando métodos de pronóstico como promedios móviles, Winters, descomposición multiplicativa, ARIMA (Box - Jenkis), Crostón y aproximación de Syntetos-Boylan (SBA) para encontrar la mejor medida de bondad de ajuste. El desempeño de cada método se evaluó a través del error porcentual absoluto (MAPE) y el error cuadrático medio (MSE). Los resultados mostraron una reducción del 60.77% del MAPE en el patrón suave y del 70.60% en el errático. Esta investigación contribuye a la literatura del sector de autopartes para apoyar en la toma de decisiones.
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Derechos de autor 2025 Erika Montes de Oca-Sánchez, Lourdes Loza-Hernández
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
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