Design of a Robotic Arm Based on a 4-DOF SCARA Configuration with a 2 m Reach and a 5 kg Load Capacity
DOI:
https://doi.org/10.70554/OBJK2026.v02n02.03Keywords:
Robotic arm, SCARA, Denavit-Hartenberg, Finite elementsAbstract
In this work we present the design of a four-degree-of-freedom robotic arm based on a SCARA-type configuration, with an approximate reach of 2.22 m and a load capacity of 5 kg, intended for the positioning and orientation of a projection system. The development of the system was carried out following Karl Ulrich's product design methodology, ranging from the definition of requirements to the validation of the prototype. The mechanical design of the manipulator was carried out using CAD tools, as well as kinematic modeling using the Denavit--Hartenberg method to determine the position and orientation of the end effector. Additionally, a structural analysis was carried out using finite element simulation in the Fusion~360 software, obtaining a minimum safety factor of 4.8 and maximum displacements of 4.464 mm, which validates the structural integrity of the system. The actuation system was designed based on the required torque analysis, implementing NEMA 24 stepper motors with timing-belt transmission that allows amplifying the torque up to 15 Nm. Finally, the Arduino-based electronic control system was developed in conjunction with the DM542 driver, allowing manual operation of the manipulator. The results obtained show the viability of the proposed design and its potential application in different environments.
References
A. G. M. A. Aziz, S. Al Dawsari, A. E. Rafaat, A. G. A. El-Magd, and A. A. Z. Diab, “A Smart Four-DOF SCARA Robot: Design, Kinematic Modeling, and Machine Learning-Based Performance Evaluation,” Automation, vol. 7, no. 1, 2026, doi: 10.3390/automation7010011.
I. Daniyan, K. Mpofu, B. Ramatsetse, and A. Adeodu, “Design and simulation of a robotic arm for manufacturing operations in the railcar industry,” Procedia Manufacturing, vol. 51, pp. 67–72, 2020, doi: 10.1016/j.promfg.2020.10.011.
G. Georgiev, G. Hristov, P. Zahariev, D. Kinaneva, V. Kolev, and R. Stewart, “Enhancing Engineering Education with Robotics: From Theory to Practice,” in Proc. 34th Annu. Conf. European Association for Education in Electrical and Information Engineering (EAEEIE), 2025, doi: 10.1109/EAEEIE65428.2025.11136346.
D. Mesa, C. Thong, C. Ranscombe, and B. Kuys, “Integrating the product development process in scientific research: Bridging the research-market gap,” Proceedings of the Design Society: International Conference on Engineering Design, pp. 2805–2814, 2019, doi: 10.1017/dsi.2019.287.
K. S. Mohamed Sahari, K. H. Weng, Y. W. Han, A. Anuar, M. Z. Baharuddin, and S. S. K. Mohideen, “Design and development of a 4-DOF SCARA robot for educational purposes,” Jurnal Teknologi (Sciences and Engineering), vol. 54, pp. 193–215, 2011, doi: 10.11113/jt.v54.810.
G. R. Ramya, N. Kanagaraj, S. Adwaitha, and S. Asok, “Empowering STEM Education Through Robotics: Tools, Applications, and Challenges,” Lecture Notes in Networks and Systems, vol. 1770, pp. 128–140, 2026, doi: 10.1007/978-3-032-14038-8_11.
L. E. Rodriguez Raygoza, J. D.-J. Lozoya-Santos, J. C. Tudon-Martinez, and L. C. Felix-Herran, “Designing the Future of ARMS Education: Integrating Industry Needs and Student Feedback into Engineering Curricula,” IFAC-PapersOnLine, vol. 59, no. 7, pp. 135–140, 2025, doi: 10.1016/j.ifacol.2025.08.036.
L. Sabat and C. K. Kundu, “History of Finite Element Method: A Review,” in Lecture Notes in Civil Engineering, vol. 75, 2021, doi: 10.1007/978-981-15-4577-1_32.
C. Sánchez-Peinado, V. Izquierdo-Álvarez, and A. M. Pinto-Llorente, “An Exploratory Study on the Integration of Programming and Robotics as Catalysts for Expanded Learning in Primary Education,” in Experiential Education for Primary Students: Excelling beyond Classroom Boundaries, pp. 219–245, 2026, doi: 10.4018/979-8-3373-5317-3.ch008.
P. V. S. Subhashini and B. A. Singh, “Analyses of a Modified SCARA Manipulator (RRRRP) for Pick and Place Application,” SSRG International Journal of Mechanical Engineering, vol. 12, no. 9, pp. 37–45, 2025, doi: 10.14445/23488360/IJME-V12I9P104.
K. Tobita, “Project-Based Learning in Robotics: Integrating Object Detection AI and Mechatronics in Undergraduate Engineering Education,” Journal of Robotics and Mechatronics, vol. 38, no. 1, pp. 35–46, 2026, doi: 10.20965/jrm.2026.p0035.
P. L. Wu, C. L. He, Z. Chang, X. L. Li, Z. Y. Ren, D. Y. Li, and C. Z. Ren, “Theoretical calculation models and measurement of friction torque for rolling bearings: State of the art,” Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 44, no. 9, 2022, doi: 10.1007/s40430-022-03726-1.
T. Zhu, F. Cai, Y. Li, and W. Liu, “Kinematics Control and Analysis of Industrial Robot,” IOP Conference Series: Materials Science and Engineering, vol. 320, no. 1, 2018, doi: 10.1088/1757-899X/320/1/012004.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Edgar Francisco Arcos Hurtado, Jhon Edwar Vargas Vásquez, Luis Enrique Rios Benitez
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The authors retain copyright and grant the journal the right to publish the work under a Creative Commons Attribution License, which allows third parties to use the published content as long as they credit the author(s) and the publication in OnBoard Knowledge Journal.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
a 