Robotic system for automated disassembly of electronic waste: Unscrewing

The increasing volume of electronic Waste from Electrical and Electronic Equipment (WEEE) presents significant environmental and economic challenges. Efficient recycling requires the disassembly of electronic devices, a process that is currently labor-intensive and costly. In this paper, we present a robotic system designed to automate the disassembly process, focusing on the task of unscrewing fasteners commonly found in electronic devices. The system integrates a Universal Robots UR10e robotic arm, an Intel RealSense D405 vision camera, and a custom-designed mechatronic screwdriver. The vision system trains several object detection models to assist robotic control and identify four different types of screw heads. The robot employs force-sensing techniques to align the screwdriver tip with the screw head before unscrewing. Validation is carried out on a real recycled hoverboard, demonstrating the system’s efficiency in automating unscrewing processes. The results can be generalized to other unscrewing operations in various industries. • Robotic system for automated disassembly, focusing on unscrewing fasteners. • The system uses a UR10e arm, a RealSense D405 camera, and a custom screwdriver. • The vision system uses a pretrained model to identify different screw head types. • Force-sensing techniques ensures precise screwdriver alignment before unscrewing. • Unscrewing efficiency was validated on a real recycled hoverboard.

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Publication Details

Journal
Robotics and Computer-Integrated Manufacturing
Published
2025-04-29
DOI
https://doi.org/10.1016/j.rcim.2025.103032
Citations
5
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
6.07
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article

Robotic system for automated disassembly of electronic waste: Unscrewing

Olatz Iparraguirre, Jorge Juan Gil, Nicolás Muñóz-Galeano, Iñaki Díaz et al.
5 citations
Robotics and Computer-Integrated Manufacturing
Robot Manipulation and Learning
6.07
article

Robotic system for automated disassembly of electronic waste: Unscrewing

Olatz Iparraguirre, Jorge Juan Gil, Nicolás Muñóz-Galeano, Iñaki Díaz, Diego Borro, F. Ricardo, Martxel Eizaguirre
article en
5 citations

Abstract

The increasing volume of electronic Waste from Electrical and Electronic Equipment (WEEE) presents significant environmental and economic challenges. Efficient recycling requires the disassembly of electronic devices, a process that is currently labor-intensive and costly. In this paper, we present a robotic system designed to automate the disassembly process, focusing on the task of unscrewing fasteners commonly found in electronic devices. The system integrates a Universal Robots UR10e robotic arm, an Intel RealSense D405 vision camera, and a custom-designed mechatronic screwdriver. The vision system trains several object detection models to assist robotic control and identify four different types of screw heads. The robot employs force-sensing techniques to align the screwdriver tip with the screw head before unscrewing. Validation is carried out on a real recycled hoverboard, demonstrating the system’s efficiency in automating unscrewing processes. The results can be generalized to other unscrewing operations in various industries. • Robotic system for automated disassembly, focusing on unscrewing fasteners. • The system uses a UR10e arm, a RealSense D405 camera, and a custom screwdriver. • The vision system uses a pretrained model to identify different screw head types. • Force-sensing techniques ensures precise screwdriver alignment before unscrewing. • Unscrewing efficiency was validated on a real recycled hoverboard.

Robotics and Computer-Integrated ManufacturingVol. 95
Centro de Estudios e Investigaciones Técnicas de Gipuzkoa (ES), Universidad de Navarra (ES)
Openalex Percentile: Top 4%
Robot Manipulation and Learning
6.07
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Robotic system for automated disassembly of electronic waste: Unscrewing — Olatz Iparraguirre, Jorge Juan Gil, et al. · Robotics and Computer-Integrated Manufacturing (2025) | TGRS Research Map | TGRS