Multi-response analysis and optimization of 3D printing process parameters for the production of CNT/ABS nanocomposites

This study investigates and optimizes the process parameters of three-dimensional printing of carbon nanotube/acrylonitrile butadiene styrene (CNT/ABS) nanocomposites with the aim of achieving an optimal balance among ultimate tensile strength, Young’s modulus, and impact energy. The statistical Taguchi method was combined with Grey Relational Analysis (GRA) to enable multi-response optimization. This integration was necessary because the mechanical properties of 3D-printed nanocomposites are interdependent and often exhibit conflicting trends; Taguchi efficiently identifies influential parameters, while GRA converts multiple responses into a single performance index, allowing simultaneous optimization. The effects of bed temperature, printing speed, layer height, wall thickness, nozzle diameter, infill density, infill pattern, and printing angle on the mechanical properties were experimentally evaluated. Mechanical tests were conducted for each response, and the Grey Relational Grade was used to rank the experiments and determine the optimal process conditions. The results indicated that infill density had the greatest impact on overall optimization, contributing nearly 75%, while layer thickness showed the most significant secondary effect at 5.06%. By integrating the three mechanical responses, the optimal parameter settings were identified to achieve the most balanced and simultaneous enhancement of tensile strength, stiffness, and impact resistance.