TY  - CHAP
A1  - Gronau, Norbert
A1  - Weber, Edzard
A1  - Wander, Paul
A1  - Ullrich, André
ED  - Plapper, Peter
T1  - A regional remanufacturing network approach
BT  - modeling and simulation of circular economy processes in the era of industry 4.0
T2  - Digitization of the work environment for sustainable production
N2  - Manufacturing companies still have relatively few points of contact with the circular economy. Especially, extending life time of whole products or parts via remanufacturing is an promising approach to reduce waste. However, necessary cost-efficient assessment of the condition of the individual parts is challenging and assessment procedures are technically complex (e.g., scanning and testing procedures). Furthermore, these assessment procedures are usually only available after the disassembly process has been completed. This is where conceptualization, data acquisition and simulation of remanufacturing processes can help. One major constraining aspect of remanufacturing is reducing logistic efforts, since these also have negative external effects on the environment. Thus regionalization is an additional but in the end consequential challenge for remanufacturing. This article aims to fill a gap by providing an regional remanufacturing approach, in particular the design of local remanufacturing chains. Thereby, further focus lies on modeling and simulating alternative courses of action, including feasibility study and eco-nomic assessment.
KW  - regional network
KW  - remanufacturing
KW  - scenario modeling
Y1  - 2022
SN  - 978-3-95545-407-4
U6  - https://doi.org/10.30844/WGAB_2022_8
SP  - 145
EP  - 170
PB  - GITO Verlag
CY  - Berlin
ER  - 
TY  - CHAP
A1  - Thim, Christof
A1  - Grum, Marcus
A1  - Schüffler, Arnulf
A1  - Roling, Wiebke
A1  - Kluge, Annette
A1  - Gronau, Norbert
ED  - Andersen, Ann-Louise
ED  - Andersen, Rasmus
ED  - Brunoe, Thomas Ditlev
ED  - Larsen, Maria Stoettrup Schioenning
ED  - Nielsen, Kjeld
ED  - Napoleone, Alessia
ED  - Kjeldgaard, Stefan
T1  - A concept for a distributed Interchangeable knowledge base in CPPS
T2  - Towards sustainable customization: cridging smart products and manufacturing systems
N2  - As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization.
KW  - learning
KW  - distributed knowledge base
KW  - artificial intelligence
KW  - CPPS
Y1  - 2021
SN  - 978-3-030-90699-3
SN  - 978-3-030-90702-0
SN  - 978-3-030-90700-6
U6  - https://doi.org/10.1007/978-3-030-90700-6_35
SP  - 314
EP  - 321
PB  - Springer
CY  - Cham
ER  -