首页 /研究 /Characterization, generative design, and fabrication of a carbon fiber-reinforced industrial robot gripper via additive manufacturing
MANIPULATION

Characterization, generative design, and fabrication of a carbon fiber-reinforced industrial robot gripper via additive manufacturing

Selim Hartomacıoğlu, Ersin Kaya, Beril Eker, Salih Dağlı, Murat Sarıkaya

发表年份
2024
引用次数
19

摘要

Robot grippers are crucial components across various industrial applications, requiring special design and production for obtaining the optimal performance. Conventional plastic injection moulding techniques fall short in achieving the specificity needed for these grippers. To address this challenge, current paper focuses on developing a robot gripper using carbon fiber-reinforced polyamide with a next-generation composite filament and employing the innovative Generative Design technique. In the work, we began by characterizing and optimizing the composite material specifications. Then, the tensile strength and fracture mechanics of standard samples based on printing parameters, applying Taguchi experimental design for optimization were evaluated. Analysis of Variance (ANOVA) was used for factor analysis to fine-tune the process. Using the Generative Design technique, we determined optimal geometries, which were then fabricated through Fused Deposition Modeling (FDM). As a result, the optimization efforts led to significant improvements i.e., tensile strength increased from 103.2 to 116 MPa, and the elasticity modulus from 8386 to 8990 MPa. In practical industrial applications, we achieved a reduction in material weight from 14 to 4 g, lowered production costs from $5.16 to $1.50, and cut production time from 58 to 28 min. This study presents a validated method for developing industrial products with reduced material usage and costs, promoting sustainable production practices.

关键词

Materials scienceCharacterization (materials science)FabricationNanotechnologyGenerative grammarComposite materialCarbon fibersMechanical engineeringManufacturing engineeringArtificial intelligence

相关论文

查看 MANIPULATION 分类全部论文