AI-based intelligent disassembly utilizing a Digital Twin (AIDDT)

Research Project, 2022 – 2023

The project aims to establish a method for AI-based intelligent disassembly of complex assembled products with a digital twin, to support the remanufacturing process and reach a circular product.
The variability and uncertainty associated with the disassembly process are essentially due to the quality of the input data, which are returned products. Therefore, in AIDDT the products need to
be measured to capture the condition of the geometry of the products. Utilizing this data, the structural behavior of the products during the disassembly process can be simulated. Furthermore, simulation-based process optimization is performed for
autonomous process control during the disassembly. Since the disassembly process involves a sequence of operations, Artificial Intelligence and Machine Learning support the sequential decision-making process autonomously for the disassembly sequence planning. AIDDT supports the quality assurance process for re-assembly of the units or reforming and remanufacturing them, which is crucial for economic and environmental sustainability.