Fraunhofer IFF develops intelligent recycling robot

Automation in electronics recycling Fraunhofer IFF develops intelligent recycling robot

2025-02-11 From Manuel Christa | Translated by AI 1 min Reading Time

The iDEAR project by Fraunhofer IFF is a recycling system consisting of various components, such as a robotic arm, 3D cameras, sensors, and, of course, AI. The goal is to achieve automatic disassembly of electronic waste.

Project iDEAR: A recycling robot automatically dismantles a PC.(Image: Fraunhofer IFF) — Project iDEAR: A recycling robot automatically dismantles a PC.
(Image: Fraunhofer IFF)

The Fraunhofer Institute for Factory Operation and Automation (IFF) in Magdeburg is working on the development of automated, non-destructive disassembly processes for electronic waste such as desktop computers within the framework of the iDEAR project. The goal is to efficiently recover valuable raw materials and strengthen the circular economy.

Growing amounts of electronic waste

Worldwide, the amount of electronic waste is continuously increasing. According to a UN report, almost 59.6 million short tons of electronic waste were produced in 2019; this number could grow to 81.7 million short tons by 2030. Most of this waste ends up in landfills or incinerators, resulting in the loss of valuable raw materials and environmental pollution.

Challenges in disassembly

The manual disassembly of electronic devices is time-consuming and costly due to the high variety of versions, complex designs, and uncertain conditions of used devices. Many devices are not designed for easy disassembly; they contain different materials and connecting elements that complicate standardized disassembly. iDEAR counters this with an individual assessment and digital disassembly planning.

Technological approaches of the robot

In the iDEAR project, researchers combine knowledge from materials science, metrology, robotics, and artificial intelligence. High-precision 3D cameras and optical sensor systems capture labels, product numbers, components, and connecting elements. Machine-learning algorithms and artificial intelligence analyze the sensor data, identify materials, and assess the condition of the components.

The initial results of the project sound promising. For example, PC cases could be automatically opened and motherboards extracted. These findings are now to be transferred to other types of devices to enable the broad application of the developed technologies in the long term. (mc)

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Date: 08.12.2025

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