Optimization in recycled vulcanized rubber - blooming reduction using response surface methodology

José de Jesús Cabrera Castro

https://orcid.org/0009-0009-6754-4460

Mexico

Centro de Innovación Aplicada en Tecnologías Competitivas

Roberto Zitzumbo Guzmán

https://orcid.org/0000-0002-4124-8825

Mexico

Centro de Innovación Aplicada en Tecnologías Competitivas image/svg+xml

Roberto Zitzumbo-Guzmán is a researcher at the Center for Applied Innovation in Competitive Technologies (CIATEC), specializing in materials development, with a solid background in polymers and composite materials. His work combines technological innovation, academic publications, and industrial applications, especially in recycling processes and statistical optimization of manufacturing. He is currently a Level 1 member of Mexico's National System of Researchers (SNII).

Luis Francisco Villalobos González

https://orcid.org/0009-0009-8417-4406

Mexico

Centro de Innovación Aplicada en Tecnologías Competitivas image/svg+xml

Luis Francisco Villalobos-González is a Research Professor at the Centro de Innovación Aplicada en Tecnologías Competitivas (CIATEC),. He did his Master and PhD studies in Science and Technology at the Centro de Innovación Aplicada en Tecnologias Competitivas. His research experience is short, but he has published three international articles. Design of experiments, robust design, polymers and the application of artificial intelligence such as neural networks and fuzzy systems are his main areas of interest. He is currently a candidate for the Mexican National System of Researchers.

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Accepted: 2025-11-12

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Published: 2026-01-12

DOI: https://doi.org/10.4995/jarte.2026.24552
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Keywords:

Optimization, recycled vulcanized rubber, response surface method, vision system, desirability function, mechanical properties

Supporting agencies:

Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCYT)

Centro de InnovaciónAplicada en Tecnologías Competitivas (CIATEC A.C.)

Abstract:

This study introduces a novel image processing–based vision system for the objective quantification of additive blooming on the surface of rubber blends containing ground tire rubber (GTR). The method applies RGB color channel decomposition to compare pre- and post-blooming states, using Euclidean distance between channels to provide a quantitative metric of blooming intensity over time.  Alongside surface analysis, mechanical characterization (tensile strength, elongation at break, and Young’s modulus) was performed to correlate blooming intensity with mechanical performance.  A central composite design (24 with 8 axial and 12 center points, including replicates) was used to evaluate the effects of formulation parameters on both blooming and key mechanical properties.  Statistical analysis revealed that blooming is mainly influenced by the additive concentration (CCA1), the vulcanizing agent (S), and their interaction, with a good model fit (R² = 81.86%, R² adj. = 76.15%). Elongation was primarily governed by the accelerator (CCD2) (R² adj. = 91.52%), while tensile strength and Young’s modulus were significantly affected by (CCD2), (S), and their interactions (R² adj. = 72.93%, R² adj. = 72.35%, respectively). The optimized formulation, which avoids redundant additive loading already present in GTR, effectively mitigates blooming without compromising mechanical performance. This approach demonstrates strong potential for sustainable rubber recycling with improved mechanical reliability and reduced surface migration. Overall, this work provides two main contributions: (i) a robust, objective methodology for blooming quantification and (ii) data-driven insights for optimizing sustainable rubber formulations, supporting the development of Industry 4.0 oriented quality control strategies.

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