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Determination of factory locations for distributed additive manufacturing, considering pollution, resilience and costs.
- Source :
- CIRP: Journal of Manufacturing Science & Technology; Jul2023, Vol. 43, p115-128, 14p
- Publication Year :
- 2023
-
Abstract
- Additive manufacturing (AM) processes with their tool-free production process and low infrastructural requirements, such as the Fused Layer Modeling process, make it possible to decentralize production capacities and thus enable distributed production. Companies and scientists expect these to increase resilience and reduce the ecological footprint. This paper focuses on the site selection of distributed additive production networks. By transforming the location planning in AM into a two-level uncapacitated facility location problem, a developed algorithmic approach based on k-means clustering can identify optimized factory distributions. This paper discusses the role and interdependence of costs, pollution and resilience in the selection process of a factory network planning. It shows the interaction between the factor costs leading to low and pollution as well as resilience leading to highly distributed manufacturing. Furthermore, possible approaches to identify optimal factory distributions, upcoming future changes in environmental politics and major advantages of distributed AM are discussed. This paper will support companies and researcher aiming for distributed resilient production using AM. The findings of this paper and parts of the approach can be used for other production technologies such as distributed production through maker spaces or factories with an equally capable machine park. Through the findings of this paper current production networks such as centralized conventional manufacturing can be compared with distributed AM networks. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 17555817
- Volume :
- 43
- Database :
- Supplemental Index
- Journal :
- CIRP: Journal of Manufacturing Science & Technology
- Publication Type :
- Academic Journal
- Accession number :
- 163550051
- Full Text :
- https://doi.org/10.1016/j.cirpj.2023.03.005