A Control Architecture for Robust and Resilient Circular Factories under Uncertain Conditions
Resource depletion and environmental harm highlight the need for more sustainable manufacturing methods like circular manufacturing. Circular manufacturing methods such as remanufacturing introduce uncertainties that arise due to core variability, leading to the frequent occurrence of disruptions. Therefore, an automated control structure is needed that can maintain stable high performance in the face of such uncertainties and disruptions. We present a novel architecture that is designed to enhance the resilience and robustness of automated circular factories. To achieve this, we propose a two-level approach resembling a cascaded control system. The outer layer, the production system level, is designed to ensure resilience by maintaining overall factory operations during larger disruptions. In contrast, the inner layer, the station level, focuses on robustness, managing minor disturbances and failures at individual stations. We address the allocation of responsibilities between these two levels and the modeling of commands. Our approach considers a novel integration of production stations, inspection stations and an intelligent intralogistics system to allow for a flexible and adaptable automated production system. Our approach presents the first control architecture specifically designed to address the unique uncertainties and disruptions arising from core variability in circular manufacturing.
Authors
- R. Wolf (ORCID: https://orcid.org/0000-0001-9456-383X)
- Yufeng Shi (ORCID: https://orcid.org/0000-0001-8784-8239)
- Gisela Lanza (ORCID: https://orcid.org/0000-0002-0481-4613)
- E Blum (ORCID: https://orcid.org/0009-0009-7930-7139)
- Jürgen Fleischer (ORCID: https://orcid.org/0000-0003-0961-7675)
- Arne Ernst (ORCID: https://orcid.org/0000-0002-7979-2578)
- Matthieu Poyer
- Nicole Stricker (ORCID: https://orcid.org/0000-0001-5367-084X)
- John B. Baumgartner (ORCID: https://orcid.org/0000-0002-8898-0300)
- Julius Pfrommer (ORCID: https://orcid.org/0000-0002-4204-6758)
- Fabian Erlenbusch (ORCID: https://orcid.org/0009-0007-8038-5797)
- Finn Bail
- R. Rayyes
Institutions
- Karlsruhe Institute of Technology (DE)
- Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (DE)
- Hochschule Aalen (DE)
Publication Details
- Journal
- Procedia CIRP
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.procir.2025.02.236
- Primary Topic
- Scheduling and Optimization Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Deutsche Forschungsgemeinschaft