Home // ADAPTIVE 2020, The Twelfth International Conference on Adaptive and Self-Adaptive Systems and Applications // View article
Authors:
Hendrik Poschmann
Holger Brüggemann
Daniel Goldmann
Keywords: disassembly; recycling 4.0; robotics; decision making; machine-learning.
Abstract:
Disassembly is an elementary process step for efficient recycling. In order to improve disassembly operations, the implementation of digitalization technologies and advanced robotic systems is investigated in this paper. The authors propose an agent-based robotic system which is capable of classifying components in a hierarchical structure for an optimized determination of an ecologically and economically feasible level of disassembly. By utilizing a machine-learning classifier, an adaptive system is facilitated being able to react to the dynamic change of conditions in the reverse supply chain. Holistic information management processes are the foundation of the advanced disassembly system. It is shown that the application of cognitive robotics fosters the progression towards an advanced circular economy by being able to reliably classify End-of-Life options autonomously.
Pages: 21 to 28
Copyright: Copyright (c) IARIA, 2020
Publication date: April 26, 2020
Published in: conference
ISSN: 2308-4146
ISBN: 978-1-61208-781-8
Location: Nice, France
Dates: from October 25, 2020 to October 29, 2020