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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA)
Sofia, R. C., Coutinho, C., Scivoletto, G., Insolvibile.G., Deshmukh, R., Schneider, A....Mastos, T. (2023). The EFPF approach to manufacturing applications across edge-cloud architectures. In Shaping the future Iot with edge intelligence: How edge computing enables the next generation of IoT applications. (pp. 319-347).: River Publishers.
Exportar Referência (IEEE)
H. R. Sofia et al.,  "The EFPF approach to manufacturing applications across edge-cloud architectures", in Shaping the future Iot with edge intelligence: How edge computing enables the next generation of IoT applications, River Publishers, 2023, pp. 319-347
Exportar BibTeX
@incollection{sofia2023_1734960863862,
	author = "Sofia, R. C. and Coutinho, C. and Scivoletto, G. and Insolvibile.G. and Deshmukh, R. and Schneider, A. and Damjanovic-Behrendt, V. and Gigante, F. and Wajid, U. and Nizamis, A. and Ioannidis, D. and Mastos, T.",
	title = "The EFPF approach to manufacturing applications across edge-cloud architectures",
	chapter = "",
	booktitle = "Shaping the future Iot with edge intelligence: How edge computing enables the next generation of IoT applications",
	year = "2023",
	volume = "",
	series = "",
	edition = "",
	pages = "319-319",
	publisher = "River Publishers",
	address = ""
}
Exportar RIS
TY  - CHAP
TI  - The EFPF approach to manufacturing applications across edge-cloud architectures
T2  - Shaping the future Iot with edge intelligence: How edge computing enables the next generation of IoT applications
AU  - Sofia, R. C.
AU  - Coutinho, C.
AU  - Scivoletto, G.
AU  - Insolvibile.G.
AU  - Deshmukh, R.
AU  - Schneider, A.
AU  - Damjanovic-Behrendt, V.
AU  - Gigante, F.
AU  - Wajid, U.
AU  - Nizamis, A.
AU  - Ioannidis, D.
AU  - Mastos, T.
PY  - 2023
SP  - 319-347
DO  - 10.13052/rp-9788770040266
AB  - Manufacturing as a Service (MaaS) refers to a set of tools and processes that can assist the shared use of networked production facilities. In the core of this paradigm is a vision where manufacturing environments shall profit from an online set of tools and services that can be tailored to the requirements coming from the different manufacturers, thus reaching a higher degree of flexibility and an increase in production efficiency.
In the context of MaaS, the Horizon 2020 European Connected Factory Platform for Agile Manufacturing (EFPF) provides an operational instantiation of a large-scale MaaS across Europe, integrating a diverse set of services such as data analytics, factory connectors, and an interoperable Data Spine to proportionate a high level of automation across different shop-floors.
This chapter explains the EFPF MaaS concept, going over its architectural design, and giving insight into how developers and SMEs can profit from the EFPF open-source SDK to generate new products, and how these products can be integrated into the EFPF broad marketplace. The chapter gives insight also to the different pilots developed in the project, explaining challenges faced, and proposed solutions.
ER  -