The Performance Analysis of The 3D Printer Corexy FDM Type With Area X=200 Y=200 Z=200 mm

  • Yuris Setyoadi Universitas PGRI Semarang
  • Rifki Hermana Universitas PGRI Semarang
Keywords: Automated machining technology, 3D Printer Corexy, 3D Printer Cartesian


A 3D printer is the result of the development of automated machining technology, which progresses from the creation of a design to the printing of a product with a complex shape and high precision for optimal printing results. The 3D printer design process begins with the creation of a design to determine the machine's dimensions, followed by the determination of specifications for the required motors, the design of electrical wiring to select the specifications for a controller, and finally, the testing of the tools when 3D printing. The accuracy of 3D corexy printers and 3D Cartesian printers are compared experimentally in this study. The printing process using a 3D printer produced two values that exceeded the tolerance limit, one in each dimension's length and width, according to the results of ten tests. The printing process results in a 3D Printer Cartesian exceeding the tolerance limit by four values: one for the length dimension, two for the width dimension, and one for the height or depth dimension. The 3D Printer Corexy is consequently more precise than the 3D Printer Cartesian because it fails less frequently.


Thomas, “GE Transportation to produce up to 250 3D printed locomotive parts by 2025,”, 2018. [Online]. Available: [Accessed: 25-Jun-2022].

D. Zhao, T. Li, B. Shen, Y. Jiang, W. Guo, and F. Gao, “A multi-DOF rotary 3D printer: machine design, performance analysis and process planning of curved layer fused deposition modeling (CLFDM),” Rapid Prototyp. J., vol. 26, no. 6, pp. 1079–1093, Jan. 2020.

S. A. Soomro and M. A. Koondhar, “The Design of Automatic Lift Control with Status Alert Capabilities Through Internet,” no. October, 2020.

N. Shahrubudin, T. C. Lee, and R. Ramlan, “An overview on 3D printing technology: Technological, materials, and applications,” Procedia Manuf., vol. 35, pp. 1286–1296, 2019.

J. C. Camargo, Á. R. Machado, E. C. Almeida, and E. F. M. S. Silva, “Mechanical properties of PLA-graphene filament for FDM 3D printing,” Int. J. Adv. Manuf. Technol., vol. 103, no. 5–8, pp. 2423–2443, 2019.

J. Scherick, C. Touchette, M. Gulbin, P. Coady, P. Radhakrishnan, and D. C. Brown, “Gapa: an Application To Assist Novice Users With 3D Printing,” ASME Int. Mech. Eng. Congr. Expo. Proc., vol. 6, 2021.

I. Pendahuluan and A. Mikrokontroler, “Penggunaan Arduino untuk Monitoring dan Otomatisasi Instrumen Penunjang Ruang Kelas,” Sci. Student J. Information, Technol. Sci., vol. 1, pp. 77–85, 2020.

B. Li, J. Liu, H. Gu, J. Jiang, J. Zhang, and J. Yang, “Structural Design of FDM 3D Printer for Low-melting Alloy,” in IOP Conference Series: Materials Science and Engineering, 2019, vol. 592, no. 1.

M. Darsin, N. A. Mahardika, G. Jatisukamto, M. Edoward, B. A. Fachri, and M. S. Hussin, “Coalesce Research Group Journal of 3D Printing and Additive Manufacturing Effect of 3D Printing Parameters on Dimensional Accuracy Using eSteel Filaments,” vol. 1, no. 1, pp. 1–7, 2021.

A. Zamheri, A. P. Syahputra, and F. Arifin, “Studi Penyusutan Pembuatan Gigi Palsu Dengan 3D Printing Fdm Pendekatan Metode Taguchi,” vol. 12, no. 2, 2020.

T. D. Ngo, A. Kashani, G. Imbalzano, K. T. Q. Nguyen, and D. Hui, “Additive manufacturing (3D printing): A review of materials, methods, applications and challenges,” Compos. Part B Eng., vol. 143, pp. 172–196, 2018.

R. A. Wicaksono, E. Kurniawan, M. K. Syafrianto, R. F. Suratman, and M. R. Sofyandi, “Rancang Bangun dan Simulasi 3D Printer Model Cartesian Berbasis Fused Deposition Modelling,” J. Engine Energi, Manufaktur, dan Mater., vol. 5, no. 2, p. 53, 2021.

I. M. Ivan WCS, M. Darsin, G. Jatisukamto, and M. S. Hussin, “Design of Portable Cartesian 3D Printer Using Arduino Mega 2560,” J. 3D Print. Addit. Manuf., vol. 1, no. 1, pp. 1–9, 2021.

Z. DeMeyer, “Arduino Mega 2560 Board: Specs, Pinout, & Capabilities,”, 2017. [Online]. Available: [Accessed: 26-Jul-2022].

Jamaaluddin, I. Robandi, I. Anshory, Mahfudz, and R. Rahim, “Application of interval type-2 fuzzy inference system and big bang big crunch algorithm in short term load forecasting new year holiday,” J. Adv. Res. Dyn. Control Syst., vol. 12, no. 2, pp. 216–226, 2020.

Marlin, “Configuring Marlin,” 2017. [Online]. Available: