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5G Enabled Manufacturing Evaluation for Data-Driven Decision-Making

Bärring, Maja, 1988 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Lundgren, Camilla, 1989 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Åkerman, Magnus, 1978 (author)
Chalmers tekniska högskola,Chalmers University of Technology
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Johansson, Björn, 1975 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Stahre, Johan, 1961 (author)
Chalmers tekniska högskola,Chalmers University of Technology
Engström, Ulrika (author)
Telefonaktiebolaget L M Ericsson,Ericsson
Friis, Martin (author)
SKF AB
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 (creator_code:org_t)
Elsevier BV, 2018
2018
English.
In: Procedia CIRP. - : Elsevier BV. - 2212-8271. ; 27, s. 266-271
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Manufacturing industries are experiencing a technical paradigm shift that will change how they run their operations. Equipment and personnel generate an ever-increasing amount of data, and connectivity enables to utilize data to a larger extent. Connecting a machine is not a technical obstacle anymore, but with all available data, the challenge is to understand the requirements of data to support efficient decision-making. This paper will address the requirements of data by domain experts, in the context of more real-time data available. A focus group interview was performed, assessing the key factors of big data; volume, velocity, and variety of data.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)

Keyword

Data-driven decision-making
Big data
5G

Publication and Content Type

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