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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Control Architecture for Robust and Resilient Circular Factories under Uncertain Conditions

R. Wolf, Yufeng Shi, Gisela Lanza, E Blum et al.
Procedia CIRP
Scheduling and Optimization Algorithms
article

A Control Architecture for Robust and Resilient Circular Factories under Uncertain Conditions

R. Wolf, Yufeng Shi, Gisela Lanza, E Blum, Jürgen Fleischer, Arne Ernst, Matthieu Poyer, Nicole Stricker, John B. Baumgartner, Julius Pfrommer, Fabian Erlenbusch, Finn Bail, R. Rayyes
article en

Abstract

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.

Procedia CIRPVol. 134
Karlsruhe Institute of Technology (DE), Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (DE), Hochschule Aalen (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 81%
Scheduling and Optimization Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.