Application of Methodologies for the Optimization of the Dyeing Process in the Textile Industry: A Systematic Review of the Literature

Zorayda Navarro Casafranca M.; Mayerly Santos Ruiz J.; Coaquira Torres E.; Enrique Cuevas Tenorio L. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2026) · DOI: 10.18687/laccei2026.1.1.1330

Resumen

This systematic literature review arises from the need to optimize the dyeing process in the textile industry, a critical stage due to its high consumption of resources and its influence on the quality of the finished product. This review aims to identify the most commonly used methodologies to improve the efficiency, color uniformity and sustainability of textile dyeing. A descriptive and qualitative methodology was applied under the PIOC model, analyzing 23 scientific articles in English and Spanish, published from 2020. During the analysis, the main shortcomings of the process were identified, such as low color fixation, excessive water and energy consumption, lack of uniformity and poor wash fastness. Among the most outstanding methodologies were the Response Surface Methodology (RSM), the use of artificial neural networks (ANN), optimization algorithms (Genetic Algorithm - GA, Particle Swarm Optimization - PSO), Lean-Green approaches and machine learning models. These tools showed significant improvements in production efficiency, cost reduction, energy savings and color accuracy. It was also shown that these methodologies were implemented in both artisanal and industrial companies, which demonstrates their versatility. Finally, the results validate that a correct selection and implementation of these methodologies contributes significantly to the optimization of the dyeing process and to the strengthening of competitiveness in the textile sector.

Instituciones: Universidad Tecnológica del Perú