Desarrollo de un gestor visual para la planeación de recursos de mantenimiento en maquinaria amarilla basado en el estándar ISO-14224

Abstract

This project addresses the development of a visual management system designed to optimize maintenance planning for heavy equipment. The work arose from the need for a tool that would centralize technical information, improve service traceability, anticipate spare parts consumption, and facilitate data-driven decision-making. To achieve this, a phased methodology was employed, progressing from technical data collection to the functional evaluation of the designed system. Initially, the technical information for the selected equipment was identified and consolidated, using manufacturer manuals and the company's operating conditions as references. Subsequently, an analysis of historical component consumption was conducted, allowing for an understanding of the actual behavior of spare parts and their relationship to maintenance cycles. This information served as the basis for establishing criticality criteria and detecting deviations between the theoretical and empirical replacement frequencies. Based on the technical and operational data, the necessary input and output parameters for the visual manager were structured, defining the fields, categories, and relationships between equipment, components, and activities. This stage allowed for the construction of a centralized database that integrates information on maintenance, inventory, material rotation, service schedules, and historical traceability. This database constitutes the functional core of the system, as it is responsible for dynamically feeding the visualizations, indicators, and automatic calculations present on the platform. In the development phase, a visual interface was designed that hierarchically presents the metrics and indicators relevant to the operation. The system allows for the automatic generation of graphs, trends, maintenance compliance percentages, consumption projections, and input availability statuses. The dashboards facilitate the consultation of fleet status and the prioritization of activities, integrating the results of the technical analysis with field information. The system automatically generates graphs, trends, maintenance compliance percentages, consumption projections, and input availability statuses. The dashboards facilitate fleet status monitoring and activity prioritization, integrating technical analysis results with field data. Finally, the visual management system's performance was evaluated by comparing it to the manual method previously used by the company. The results showed significant improvements in efficiency, accuracy, and processing time, while also identifying opportunities for improvement aimed at strengthening operational data capture and expanding the system's functionalities. The project demonstrates that the integration of technical analysis, data processing, and a visual interface directly contributes to optimized maintenance and informed decision-making