MELHORIA DO PROCESSO DE DEGOMAGEM ENZIMÁTICA EM UMA INDÚSTRIA DE ÓLEO DE SOJA

Abstract

This study evaluates the enzymatic degumming process in a soybean oil refinery with the aim of optimizing product yield and quality. Operational and quality variables such as process temperatures, flow rate, phosphorus content, and gum moisture were analyzed. Data were collected in real-time at critical points in the production line, enabling the calculation of theoretical, moisture-based, and actual losses based on mass balance. Descriptive statistics, Pearson correlation, and linear regression methods were employed for the analysis using Microsoft Excel and Minitab software. The results highlighted significant relationships between key variables, such as residual gum quality, input phosphorus content, process levels, and temperatures, indicating opportunities for operational adjustments to minimize losses. The in depth statistical analysis provided valuable insights for managerial decision-making, enabling the implementation of specific interventions that enhanced process efficiency and consistency. It is concluded that integrating managerial analysis with statistical tools is essential for identifying inefficiencies and improving process performance, ensuring greater competitiveness in the production of high-quality refined soybean oil.