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3D printing technology is a widely preferred industrial production method in various fields such as automotive, biomedical, medical and aerospace-defense for modeling physical objects, rapid prototyping of complex structures. Fused deposition modeling (FDM) technology, one of the 3D printing methods, produces durable and dimensionally stable parts with the best accuracy and maintainability than other existing 3D printing technologies. The printing parameters are very important in part production with 3D printing technology. In this study, two critical printing parameters such as 3D printing filling rate and nozzle temperature were investigated. Fuzzy logic-based modeling method was used to understand the relationship between these parameters and the tensile strength of the samples produced with thermoplastic polyurethanes (TPU) using FDM technique. With fuzzy logic, the tensile strength was predicted with high accuracy. As a result, the model and experimental results were found to be compatible.

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Prediction of Tensile Strength with Fuzzy Logic Approach for Fused Deposition Modelling of TPU Materials

  • 会议论文

  • 发表日期：

    2025年

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  • Koray Ozsoy,
  • Bekir Aksoy

摘要

3D printing technology is a widely preferred industrial production method in various fields such as automotive, biomedical, medical and aerospace-defense for modeling physical objects, rapid prototyping of complex structures. Fused deposition modeling (FDM) technology, one of the 3D printing methods, produces durable and dimensionally stable parts with the best accuracy and maintainability than other existing 3D printing technologies. The printing parameters are very important in part production with 3D printing technology. In this study, two critical printing parameters such as 3D printing filling rate and nozzle temperature were investigated. Fuzzy logic-based modeling method was used to understand the relationship between these parameters and the tensile strength of the samples produced with thermoplastic polyurethanes (TPU) using FDM technique. With fuzzy logic, the tensile strength was predicted with high accuracy. As a result, the model and experimental results were found to be compatible.