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A Big Data Platform for Industrial Enterprise Asset Value Enablers

  • 2019
  • OriginalPaper
  • Chapter
Published in:
Authors
Alda Canito
Marta Fernandes
Luís Conceição
Isabel Praça
Goreti Marreiros
Published in
Distributed Computing and Artificial Intelligence, 15th International Conference
Publisher
Springer International Publishing

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Abstract

The growing ubiquity of IoT, along with bigger steps towards full digitalization in the manufacturing industry, makes it easier to constantly monitor equipment activity and implement predictive maintenance approaches. Big Data solutions are best suited to process the large amounts of data generated through monitorization – additionally, they also allow for processing of unstructured data, such as documents used in not fully-digitalized processes. This paper describes the creation of a small Hadoop cluster, without high-availability, its integration in the InValue architecture and the processes through which it was populated with historical data from a relational warehouse. The degree of parallelization on the data ingestion tasks and its effect on performance were evaluated for the different kinds of datasets that are currently being used for batch data processing.

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previous chapter Recognizing the Order of Four-Scene Comics by Evolutionary Deep Learning
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Title
A Big Data Platform for Industrial Enterprise Asset Value Enablers
Authors
Alda Canito
Marta Fernandes
Luís Conceição
Isabel Praça
Goreti Marreiros
Copyright Year
2019
Publisher
Springer International Publishing
Book
Distributed Computing and Artificial Intelligence, 15th International Conference

Print ISBN: 978-3-319-94648-1

Electronic ISBN: 978-3-319-94649-8

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-94649-8_18
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