Book chapter
The EFPF approach to manufacturing applications across edge-cloud architectures
Rute C. Sofia (Sofia, R. C.); Carlos Coutinho (Coutinho, C.); Gabriele Scivoletto (Scivoletto, G.); Gianluca Insolvibile (Insolvibile.G.); Rohit Deshmukh (Deshmukh, R.); Alexander Schneider (Schneider, A.); Violeta Damjanovic-Behrendt (Damjanovic-Behrendt, V.); Fernando Gigante (Gigante, F.); Usman Wajid (Wajid, U.); Alexandros Nizamis (Nizamis, A.); Dimosthenis Ioannidis (Ioannidis, D.); Theofilos Mastos (Mastos, T.); et al.
Book Title
Shaping the future Iot with edge intelligence: How edge computing enables the next generation of IoT applications
Year (definitive publication)
2023
Language
English
Country
Denmark
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Abstract
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.
Acknowledgements
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Keywords
MaaS,machine learning,IIoT,federated platform,SDK
  • Computer and Information Sciences - Natural Sciences
  • Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
Funding Records
Funding Reference Funding Entity
H2020 - 825075 European Commission

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