Overview
Robotic Disassembly |
Business Viewpoint
Remanufacturing can use as little as 10 per cent of the energy and raw materials required to build the product from scratch. It can also reduce CO2 emissions by more than 80 per cent. |
Stakeholder Viewpoint
Manufacturers: Manufacturers benefit from robotic disassembly by facilitating product end-of-life management, reducing waste generation, and complying with environmental regulations. Robotic disassembly systems allow manufacturers to recover valuable materials from returned or obsolete products, minimize disposal costs, and enhance their reputation for sustainability. Recyclers: Recyclers benefit from robotic disassembly by automating the separation and sorting of materials from electronic waste, automotive components, or other products. Robotic disassembly systems improve the efficiency and accuracy of material recovery processes, enabling recyclers to recover higher-value materials and reduce processing costs. |
Technology Viewpoint
Robotic Manipulators: Industrial robots are equipped with robotic arms, grippers, and end-effectors designed to handle a wide range of products or components. These robots are programmed to perform disassembly tasks such as dismantling, unscrewing, cutting, or extracting parts from assemblies. Sensors and Vision Systems: Robotic disassembly systems use sensors and vision systems to detect part orientation, identify fasteners, and monitor the disassembly process in real-time. Cameras, proximity sensors, and laser scanners provide feedback to the control system, enabling robots to adapt to variations in part geometry and surface characteristics.
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Data Viewpoint
Material Identification: Robotic disassembly systems use sensors, cameras, and artificial intelligence algorithms to identify and classify materials such as metals, plastics, and electronic components. This data enables precise sorting and separation of materials for recycling or remanufacturing purposes. Process Optimization: Data collected from robotic disassembly systems can be analyzed to optimize process parameters, improve equipment utilization, and minimize downtime. Predictive maintenance algorithms can anticipate equipment failures and schedule maintenance activities to prevent unplanned downtime and ensure reliable operation. |
Deployment Challenges
Facility Layout: Robotic disassembly systems are integrated into existing recycling or remanufacturing facilities, requiring careful consideration of layout, workflow, and material flow. Equipment placement, conveyor systems, and material handling processes are optimized to maximize efficiency and minimize bottlenecks. Training and Maintenance: Deploying robotic disassembly systems involves training operators and maintenance personnel to operate and maintain robotic equipment safely and effectively. Ongoing training and support are provided to ensure that employees can troubleshoot issues, perform routine maintenance tasks, and optimize system performance. |