ISSN: 3048-6939

A Virtual 3D Printer Model for Robotic System Design in CoppeliaSim (P6-P10)

Abstract

3D printers are gaining significant popularity in diverse fields, especially for prototyping and product development. However, physical 3D printers are expensive, bulky, and challenging to transport, which poses difficulties for researchers who need access to these devices for testing algorithms and prototypes. This research proposes an alternative solution by leveraging the CoppeliaSim simulator to create a virtual 3D printer model. Using the popular and affordable Ender 3D printer specifications, we build a detailed simulation of the printer within CoppeliaSim, a powerful open-source robotics simulation environment. The process is simplified through a step-by-step guide, allowing researchers to quickly create the model, control it with LUA scripting, and simulate printing tasks such as drawing a square on the print bed. All relevant project files and code are made available on GitHub, enabling researchers to easily download and integrate the model into their own work. The simulation provides an accessible platform to test 3D printing algorithms, analyse 3D print files, and explore printer functionality without the physical constraints of a real printer. Researchers can further adapt the model by modifying physical parameters or designing custom 3D printers. This method offers a cost-effective, flexible, and practical solution for 3D printing research, allowing faster iteration and experimentation, particularly for those with limited resources or space.

References

  1. Anderson, C. (2012). Makers: The New Industrial Revolution. Crown Business
  2. Choi, S. H., & Ahn, S. H. (2019). Improving the accuracy of 3D printing simulation for research applications. Journal of Manufacturing Processes, 41, 303-312. https://doi.org/10.1016/j.jmapro.2019.07.024
  3. 1. M. Ravichand, Kapil Bansal, G. Lohitha, R. J. Anandhi, Lovi Raj Gupta, Patel Chaitali Mohanbhai, Narendra Kumar: Research on Theoretical Contributions and Literature-Related Tools for Big Data Analytics, Recent Trends In Engineering and Science for Resource Optimization and Sustainable Development, https://www.taylorfrancis.com/chapters/edit/10.1201/9781003596721-51/research-theoretical-contributions-literature-related-tools-big-data-analytics-ravichand-kapil-bansal-lohitha-anandhi-lovi-raj-gupta-patel-chaitali-mohanbhai-narendra-kumar?context=ubx&refId=00e3f2ad-b5fc-4530-89ae-1ac3269e9566
  4. 2. E. Mythily, S. S. Ramya, K. Sangeeta, B Swathi, Manish Kumar, Purnendu Bikash, Narendra Kumar: Think Big with Big Data: Finding Appropriate Big Data Strategies for Corporate Cultures, Recent Trends In Engineering and Science for Resource Optimization and Sustainable Development, https://www.taylorfrancis.com/chapters/edit/10.1201/9781003596721-46/think-big-big-data-finding-appropriate-big-data-strategies-corporate-cultures-mythily-ramya-sangeeta-swathi-manish-kumar-purnendu-bikash-narendra-kumar?context=ubx&refId=0535aba0-a7b3-4325-b543-79aa313a2168
  5. Fink, J., & Eisen, G. (2021). Virtual versus physical prototyping: A comparative analysis of cost-effectiveness in 3D printing research. Journal of Engineering Design and Automation, 29(2), 145-160. https://doi.org/10.1080/15394301.2021.1919153
  6. Gunasekaran, A., & Yusuf, Y. (2017). A review of simulation in 3D printing research: Applicability, limitations, and opportunities. International Journal of Advanced Manufacturing Technology, 91(5-8), 2205-2216. https://doi.org/10.1007/s00170-017-0421-3
  7. Kermani, S., & Agarwal, A. (2020). Advances in 3D printing and simulation tools for industrial applications: A comprehensive review. International Journal of Computer Integrated Manufacturing, 33(3), 238-258. https://doi.org/10.1080/0951192X.2020.1721417
Download PDF

How to Cite

Krishan kumar Yadav, (2025/4/28). A Virtual 3D Printer Model for Robotic System Design in CoppeliaSim. JANOLI International Journal of Applied Engineering and Management, Volume D0yPfb5bqzwnvXQdjUkv, Issue 2.