Exploring in the Application Slicing Technology to Determine Spatial Information to Assist and Facilitate Robotic Disassembly

As lowering manufacturing cost and improving resource sustainability is becoming more critical, remanufacturing has attained significant attention in the manufacturing industry. Disassembly is the first step and consumes the most time in remanufacturing. There are three ways to disassemble a part and they are: manual disassembly (MD), human–robot collaborative disassembly (HRCD), and robotic disassembly (RD). RD is a disassembly method using robots without any human intervention and is the focus of this research work. To implement RD, spatial information is crucial. As end-of-life (EOL) products are likely to be discontinued products, the digital models for these products are not likely to be available and determining spatial information using vision systems to facilitate RD may not be possible due to occlusion and inaccessibility caused by restrictive spatial environments such as car under bonnet. However, a digital model of EOL products (including their internal profiles) can be obtained using 3D scan or computed tomography (CT) scan and subsequently, sliced into layers to determine essential spatial information to facilitate RD. Therefore, this research work has proposed to explore the application of slicing technology to assist the RD of a car battery within a car engine compartment where a scanned digital model of the car engine (under the bonnet compartment) is sliced into layers and exported as a text file known as geometry-code (G-code) that contains a large amount of geometrical information that can be used to determine the geometry, location of each component and spatial availability information of an EOL product. The results show that the x, y, z coordinates extracted from G-code can be used to define the spatial availability and identify the barriers and facilitate the creation of collision free paths for RD.