Diseño de un modelo de planificación de personal y tareas para una línea de procesamiento de carne de cerdo

Abstract

CONDITION FOR PUBLICATION OF PROJECT. In the food industry, particularly in pork cold-processing plants, staff allocation is a critical factor to ensure efficiency, quality, and compliance with production schedules. This project aims to design and implement an automated personnel allocation model, under the hypothesis that data-driven planning enhances task distribution, reduces overtime, and optimizes resource usage. The justification lies in the fact that current manual methods fail to adequately address demand fluctuations and unexpected events, leading to imbalances in workload distribution. For the development, the current planning process was analyzed, identifying critical tasks such as cutting, weighing, packaging, and storage, and a model was subsequently designed to link production volume with the required number of workers per task, considering shift constraints and operational capacity. Validation with real plant data showed a projected 15% reduction in overtime and an improvement in workload balance. In conclusion, the automated model is an effective tool that contributes to operational efficiency, resource optimization, and process sustainability. Keywords: staff allocation, operational efficiency, sustainability, resource optimization, food industry.