Design and Development of a Mini Excavator as Innovative Learning Media
Abstract
The rapid advancement of mechanical and electronic engineering, particularly in heavy equipment and construction automation, requires innovative learning media that effectively bridge theoretical knowledge and practical implementation. Conventional instructional methods often provide limited opportunities for students to develop hands-on experience with complex mechatronic systems. This study presents the design, development, and evaluation of a miniature battery-electric excavator intended as an educational platform for teaching construction robotics, automation, and sustainable engineering principles. The development process followed a structured methodology consisting of conceptual design, mechanical fabrication, electronic integration, simulation, and functional testing. Unlike conventional excavators that rely on hydraulic actuators, the proposed system employs electric motors to drive the boom, arm, and bucket mechanisms, demonstrating an energy-efficient and environmentally friendly alternative. Locomotion is achieved using DC gearbox motors for wheel movement, while an independent DC motor enables 90° rotational motion. The control architecture is based on an Arduino Mega microcontroller integrated with a wireless PS2 joystick, providing intuitive and precise user control. Lightweight aluminum was selected for the backhoe assembly to reduce overall weight, whereas the main chassis was constructed from mild steel to ensure structural strength and operational stability. Experimental evaluation confirmed that the prototype successfully performed essential excavation motions, achieving a maximum horizontal reach of 1,400 mm, a vertical reach of 1,420 mm, an average operating speed of 0.5 m/s, and a maximum speed of 1.0 m/s. With compact dimensions of 800 × 600 × 750 mm, the system is safe, portable, and suitable for laboratory-based education. Furthermore, the platform supports Deep Neural Network (DNN) data generation and reinforcement learning research, providing a cost-effective and safe environment for advancing student competencies in intelligent construction technologies
Keywords
References
I. Tselios and P. G. Nikolakopoulos, “Vibration analysis of a functionally Graded cracked shaft system and AI-based design optimization,” Applications in Engineering Science, vol. 25, Mar. 2026, doi: 10.1016/j.apples.2025.100282.
D. A. Shibanov, S. L. Ivanov, and P. V. Shishkin, “Digital technologies in modeling and design of mining excavators,” in Journal of Physics: Conference Series, IOP Publishing Ltd, Feb. 2021. doi: 10.1088/1742-6596/1753/1/012052.
Z. Zhang, M. Talib, Y. Zhang, K. Cheng, B. Tabassum, and X. Ji, “Torque prediction theory and its application for full-face rock tunnel boring machine,” Chinese Journal of Mechanical Engineering, vol. 39, p. 100006, Jan. 2026, doi: 10.1016/j.cjme.2025.100006.
Y. Tan et al., “Dynamic simulation analysis of working equipment of small backhoe hydraulic excavator,” in Journal of Physics: Conference Series, Institute of Physics, 2024. doi: 10.1088/1742-6596/2691/1/012007.
J. Nevrly et al., “Battery Electric Drive of Excavator Designed with Support of Computer Modeling and Simulation,” MDPI AG, Nov. 2020, p. 25. doi: 10.3390/wef-06927.
H. Zhou, W. Li, T. Poulet, H. Basarir, and A. Karrech, “Life cycle assessment of recycling lithium-ion battery related mineral processing by-products: A review,” Mar. 01, 2024, Elsevier Ltd. doi: 10.1016/j.mineng.2024.108600.
S. F. Saffari, D. Kim, and B. Choi, “Robotization of Miniature-Scale Radio-Controlled Excavator: A New Medium for Construction- Specific DNN Data Generation,” IEEE Access, vol. 13, pp. 17054–17067, 2025, doi: 10.1109/ACCESS.2025.3532203.
P. Flores, “A bibliometric overview of Mechanism and Machine Theory journal: Publication trends from 1990 to 2020,” Mech. Mach. Theory, vol. 175, Sep. 2022, doi: 10.1016/j.mechmachtheory.2022.104965.
Á. Semjén and J. Szép, “Integrating generative and parametric design with BIM: A literature review of challenges and research gaps in construction design,” Applications in Engineering Science, vol. 23, Sep. 2025, doi: 10.1016/j.apples.2025.100253.
S. Yao et al., “Towards understanding the geometric error coupling effect on squareness error identification in circular tests,” Mech. Mach. Theory, vol. 211, p. 106045, Sep. 2025, doi: 10.1016/j.mechmachtheory.2025.106045.
K. P. Galvin, M. Guner, and P. Kowalczuk, “Comments On: Impact assessment and optimization of REFLUX flotation cell (RFC) primary settings on copper sulfide ore flotation (Guner and Kowalczuk, Minerals Engineering, 233, 109653, 2025),” Miner. Eng., vol. 235, Jan. 2026, doi: 10.1016/j.mineng.2025.109895.
Q. Lou and J. Kövecses, “Slip decomposition and state estimation for rovers,” Mech. Mach. Theory, vol. 221, May 2026, doi: 10.1016/j.mechmachtheory.2026.106382.
X. Li, Z. Sun, H. Qi, Y. Guo, and S. Bai, “Analysis method for evaluating uncertainty in the machining process of thin-walled parts,” Chinese Journal of Mechanical Engineering, p. 100250, Feb. 2026, doi: 10.1016/j.cjme.2026.100250.
L. Piancastelli, I. Giusti, and M. De Santis, “Assessment of main bearing displacements in the monoblock of a commercial common rail diesel engine,” Applications in Engineering Science, vol. 24, Dec. 2025, doi: 10.1016/j.apples.2025.100254.
D. Mesa et al., “Strontium minerals as critical raw materials — Market dynamics, processing techniques, and future challenges,” Jan. 01, 2025, Elsevier Ltd. doi: 10.1016/j.mineng.2024.109065.
H. Xu, Y. Cai, and S. Bi, “Improving surface quality and profile accuracy of five-axis machining via vector error coupling modeling and compensation,” Chinese Journal of Mechanical Engineering, p. 100217, Jan. 2026, doi: 10.1016/j.cjme.2026.100217.
X. Yue, H. Chen, H. Bian, X. Yang, J. Han, and S. Zang, “High-quality and high-precision machining of small hole with large aspect ratios using variable-parameter composite EDM/ECM processes with speed limit,” Chinese Journal of Mechanical Engineering, p. 100147, Oct. 2025, doi: 10.1016/j.cjme.2025.100147.
Y. Dong et al., “Design and fabrication of foam-filled topology optimized composite structures using an improved non-monotonic interpolation function,” Applications in Engineering Science, vol. 21, Mar. 2025, doi: 10.1016/j.apples.2025.100205.
D. E. P. Klenam et al., “Additive manufacturing: shaping the future of the manufacturing industry – overview of trends, challenges and opportunities,” Applications in Engineering Science, vol. 22, Jun. 2025, doi: 10.1016/j.apples.2025.100224.
L. Hua, J. Pi, L. Yu, H. Liu, N. Huang, and L. Zhu, “fAccurate five-axis toolpath interpolation with kinematic corner smoothing subject to tangential and axial kinematic constraints for high-quality machining,” Chinese Journal of Mechanical Engineering, p. 100276, Mar. 2026, doi: 10.1016/j.cjme.2026.100276.
D. Wei, A. Otemissov, X. Mandaiye, and S. Zhao, “Optimal structural design of helical springs with Ludwik-type elastic–plastic materials,” Applications in Engineering Science, vol. 24, Dec. 2025, doi: 10.1016/j.apples.2025.100259.
DOI: https://doi.org/10.52088/ijesty.v6i3.1775
Refbacks
- There are currently no refbacks.
Copyright (c) 2026 Abdul Tahir, Irdam, Jasman, Musakirawati
The works in the IJESTY Journal are licensed under a Creative Commons Attribution 4.0 International Public License (CC BY 4.0).