Additive manufacturing has greatly improved rapid prototyping and small-scale production, but post-processing steps such as support removal, surface finishing, and print-bed cleaning remain largely manual and labor-intensive. These tasks introduce inefficiencies, inconsistencies in product quality, and potential safety risks due to exposure to chemicals like acetone used in vapor smoothing. Scrappy addresses this problem by developing a robotic system capable of automating these post-processing operations. By reducing manual labor and human exposure to hazardous materials, the project aims to improve safety, repeatability, and overall efficiency within additive manufacturing workflows.
Scrappy uses the AR4 MK3 six-axis robotic arm as the primary hardware platform to automate post-processing tasks for 3D printed parts. The system integrates stepper motors, motor drivers, limit switches, and motor encoders to enable precise robotic manipulation and safe operation. Control software is developed in Python and runs on an Ubuntu-based system, enabling motion planning, trajectory generation, and automated support detection algorithms. Additionally, the Ray distributed computing framework is used to manage concurrent processes and coordinate robotic control tasks.
Scrappy successfully integrated the AR4 MK3 robotic arm hardware platform, including stepper motors, motor drivers, and electrical control components. Six limit switches were installed and validated to prevent mechanical overtravel and ensure safe operation. Initial testing confirmed coordinated multi-axis motion and stable electrical performance of the robotic system. These results demonstrate that the platform is ready for future development stages, including automated toolpath generation, sensor-guided manipulation, and fully autonomous post-processing operations.