Scalable data pipeline architecture to support the industrial internet of things
Autor: | Rishabh Venketesh, Moneer Helu, Daniel Hartenstine, Timothy Sprock, William Sobel |
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Rok vydání: | 2020 |
Předmět: |
0209 industrial biotechnology
Process (engineering) Computer science business.industry Mechanical Engineering Pipeline (computing) 02 engineering and technology Feature scaling Data science Industrial and Manufacturing Engineering Variety (cybernetics) 020303 mechanical engineering & transports 020901 industrial engineering & automation Data access 0203 mechanical engineering Analytics Scalability Architecture business |
Zdroj: | CIRP Annals. 69:385-388 |
ISSN: | 0007-8506 |
Popis: | Managing manufacturing data remains challenging despite the growth of the Industrial Internet of Things (IIoT). While various standards and technologies enable greater access to data, scaling data processing and distribution can be difficult given the increasing variety of data from an increasing variety of sources in global production networks. This paper proposes an architecture for a scalable pipeline to process and distribute data from a mix of shop-floor sources. The feasibility of this approach is explored by implementing the architecture to bring together MTConnect-compliant machine and ad-hoc power data to support analytics applications. |
Databáze: | OpenAIRE |
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