Implementación del sistema OEE como herramienta para la mejora continua en la máquina pba de Niuform.
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Date
2025
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Universidad de Concepción
Abstract
Este estudio tiene como finalidad implementar un sistema de medición de desempeño en la máquina PBA (Portalbearbeitungszentrum, es español Centro de mecanizado de pórtico) es de la planta Niuform, perteneciente al grupo CMPC, mediante la aplicación del indicador OEE (Overall Equipment Effectiveness). Esta herramienta, ampliamente validada en contextos industriales, permite cuantificar la eficiencia de un equipo a partir de tres componentes fundamentales: disponibilidad, rendimiento y calidad. La motivación principal del estudio surge de la necesidad de abordar una problemática concreta observada en planta: la ausencia de un sistema estructurado que permita monitorear, analizar y mejorar el desempeño de equipos críticos como la PBA, cuya eficiencia impacta directamente en el flujo operativo y en los resultados productivos generales.
El proyecto se desarrolló en un contexto operativo complejo, con registros dispersos y gestionados informalmente. Mediante el análisis de datos históricos, un protocolo de recolección estructurado y un dashboard en Power BI, se consolidó una plataforma clara y orientada a la toma de decisiones. El sistema incluyó la depuración y modelado de datos de producción, tiempos muertos y rechazos, enfocados exclusivamente en la PBA.
El análisis de los resultados evidenció que la principal limitante en el desempeño de la máquina no corresponde a problemas de calidad ni de velocidad de trabajo, sino a una baja disponibilidad operativa causada por altos niveles de tiempo muerto. El OEE global promedio del periodo analizado (octubre 2024 – abril 2025) fue de 49,19 %, clasificado como deficiente, con una disponibilidad media de 53,10 %, un rendimiento de 93,09 % y una calidad de 99,52 %. Más del 80 % del tiempo muerto se concentró en diez causas críticas, destacando ajustes operacionales, volteo de producto y retiro de producto, todas de origen interno y, por lo tanto, abordables mediante mejoras de gestión.
A partir del diagnóstico, se diseñó un plan de mejora enfocado en las diez causas más frecuentes de tiempo perdido, proponiendo acciones específicas para cada una, tales como pautas operativas, micro observaciones, estandarización de rutinas, mejoras en la coordinación y mecanismos de seguimiento. Las propuestas buscan reducir la variabilidad operativa, recuperar capacidad instalada y establecer una cultura de mejora continua basada en evidencia objetiva. En definitiva, esta tesis no solo entrega un diagnóstico técnico del comportamiento de la PBA, sino que además deja instaladas herramientas concretas para gestionar el desempeño de manera más eficiente y replicable en otros equipos de planta.
This study aims to implement a performance measurement system for the PBA (Portalbearbeitungszentrum, or Gantry Machining Center) machine at the Niuform plant, part of the CMPC group, through the application of the OEE (Overall Equipment Effectiveness) indicator. This tool, widely validated in industrial contexts, quantifies the efficiency of a piece of equipment based on three fundamental components: availability, performance, and quality. The main motivation for the study arises from the need to address a specific issue observed at the plant: the absence of a structured system to monitor, analyze, and improve the performance of critical equipment such as the PBA, whose efficiency directly impacts the operational flow and overall production result. The project was developed in a complex operational context, with records dispersed and informally managed. Through historical data analysis, a structured data collection protocol, and a Power BI dashboard, a clear and decision-oriented platform was consolidated. The system included the cleaning and modeling of production, downtime, and rejection data, focusing exclusively on the PBA. The analysis of the results showed that the main limitation in the machine’s performance is not related to quality issues or working speed, but rather to low operational availability caused by high levels of downtime. The average global OEE for the period analyzed (October 2024 – April 2025) was 49.19%, classified as poor, with an average availability of 53.10%, a performance of 93.09%, and a quality of 99.52%. More than 80% of the downtime was concentrated in ten critical causes, notably operational adjustments, product flipping, and product removal, all of internal origin and therefore addressable through management improvements. Based on the diagnosis, an improvement plan was designed focusing on the ten most frequent causes of lost time, proposing specific actions for each, such as operational guidelines, micro-observations, routine standardization, coordination improvements, and monitoring mechanisms. These proposals aim to reduce operational variability, recover installed capacity, and establish a culture of continuous improvement based on objective evidence. Ultimately, this thesis not only provides a technical diagnosis of the PBA’s behavior but also implements concrete tools to manage performance more efficiently and in a way that can be replicated in other plant equipment.
This study aims to implement a performance measurement system for the PBA (Portalbearbeitungszentrum, or Gantry Machining Center) machine at the Niuform plant, part of the CMPC group, through the application of the OEE (Overall Equipment Effectiveness) indicator. This tool, widely validated in industrial contexts, quantifies the efficiency of a piece of equipment based on three fundamental components: availability, performance, and quality. The main motivation for the study arises from the need to address a specific issue observed at the plant: the absence of a structured system to monitor, analyze, and improve the performance of critical equipment such as the PBA, whose efficiency directly impacts the operational flow and overall production result. The project was developed in a complex operational context, with records dispersed and informally managed. Through historical data analysis, a structured data collection protocol, and a Power BI dashboard, a clear and decision-oriented platform was consolidated. The system included the cleaning and modeling of production, downtime, and rejection data, focusing exclusively on the PBA. The analysis of the results showed that the main limitation in the machine’s performance is not related to quality issues or working speed, but rather to low operational availability caused by high levels of downtime. The average global OEE for the period analyzed (October 2024 – April 2025) was 49.19%, classified as poor, with an average availability of 53.10%, a performance of 93.09%, and a quality of 99.52%. More than 80% of the downtime was concentrated in ten critical causes, notably operational adjustments, product flipping, and product removal, all of internal origin and therefore addressable through management improvements. Based on the diagnosis, an improvement plan was designed focusing on the ten most frequent causes of lost time, proposing specific actions for each, such as operational guidelines, micro-observations, routine standardization, coordination improvements, and monitoring mechanisms. These proposals aim to reduce operational variability, recover installed capacity, and establish a culture of continuous improvement based on objective evidence. Ultimately, this thesis not only provides a technical diagnosis of the PBA’s behavior but also implements concrete tools to manage performance more efficiently and in a way that can be replicated in other plant equipment.
Description
Tesis presentada para optar al título de Ingeniero/a Civil Industrial.
Keywords
Estudiantes de ingeniería Investigaciones Chile, Orientación vocacional, Universidades