Paper Info
Title
Concept of an agile production system based on learning robots applied to disassembly
Abstract
Agile production systems combine a high degree of flexibility and adaptability. These qualities are particularly crucial in an environment with high uncertainty, for example in the context of remanufacturing. Remanufacturing describes the industrial process of reconditioning used parts so that they regain comparable technical properties as new parts. Due to the scarcity of resources and regulatory requirements, the importance of remanufacturing is increasing. Due to the unpredictable component properties, automation plays a subordinate role in remanufacturing. The authors present a concept how automated disassembly can be achieved even for components of uncertain specifications by using artificial intelligence. For the autonomous development of disassembly capabilities, digital twins are used as learning environments. On the other hand, skills and problem-solving strategies are identified and abstracted from human observation. To achieve an efficient disassembly system, a modular station concept is applied, both on the technical and on the information technology level.
Year
DOI
Venue
2022
10.1515/auto-2021-0158
AT-AUTOMATISIERUNGSTECHNIK
Keywords
DocType
Volume
remanufacturing, automation, machine learning
Journal
70
Issue
ISSN
Citations 
6
0178-2312
0
PageRank 
References 
Authors
0.34
0
20
Name
Order
Citations
PageRank
Gisela Lanza100.34
tamim asfour21889151.86
Juergen Beyerer300.34
Barbara Deml400.34
Juergen Fleischer500.34
Michael Heizmann600.34
Kai Furmans700.34
Constantin Hofmann800.34
Alexander Cebulla900.34
Christian Dreher1000.34
Jan-Philipp Kaiser1100.34
Jan-Felix Klein1200.34
Fabian Leven1300.34
Simon Mangold1400.34
Norbert Mitschke1500.34
Nicole Stricker1600.34
Julius Pfrommer1700.34
Chengzhi Wu1800.34
Marco Wurster1900.34
Manuel Zaremski2000.34