Modelo de optimización para la evaluación de la eficiencia en el proceso de moldeo por inyección para la producción de botas termoplásticas.

Abstract

The PVC footwear industry faces the challenge of maintaining high levels of productive efficiency in a competitive environment, where uncontrolled variability in injection processes compromises quality and productivity. In this context, this research aimed to optimize the injection molding process for the production of thermoplastic boots at Plasticaucho Industrial S.A., through the reduction of cycle times, the decrease of defects, and the improvement of productivity. The methodology combined Statistical Process Control (SPC) on 3,260 historical data from the January–March 2026 period, the formulation of a Mixed Integer Linear Programming (MILP) optimization model with twelve decision variables, and the estimation of production and defect equations through multiple linear regression in R on 1,271 paired records, reaching a coefficient of determination R² = 0.83 (p < 0.001). The most relevant results indicate that the model project’s productivity increases between 10% and 31%, and defect reductions between 42% and 100%, depending on the machine. Among the optimal parameters identified are a pressure of 0 Bar in the shaft injector and 10 Bar in the sole injector for the three machines, as well as Zone 3 temperatures differentiated by injector. The sensitivity analysis identified the Zone 3 temperature of the sole injector as the most influential variable (elasticity 0.80). These findings position the MILP model as a decision-making support tool and a means for process standardization, highlighting the importance of data-driven management over empirical operator adjustments, and providing applied evidence in an Ecuadorian industrial context with limited empirical literature.