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A Taxonomy for Combining Activity Recognition and Process Discovery in Industrial Environments

Sammendrag

Despite the increasing automation levels in an Industry 4.0 scenario, the tacit knowledge of highly skilled manufacturing workers remains of strategic importance. Retaining this knowledge by formally capturing it is a challenge for industrial organisations. This paper explores research on automatically capturing this knowledge by using methods from activity recognition and process mining on data obtained from sensorised workers and environments. Activity recognition lifts the abstraction level of sensor data to recognizable activities and process mining methods discover models of process executions. We classify the existing work, which largely neglects the possibility of applying process mining, and derive a taxonomy that identifies challenges and research gaps.
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Kategori

Vitenskapelig artikkel

Oppdragsgiver

  • EC/H2020 / 723737

Språk

Engelsk

Forfatter(e)

  • Felix Mannhardt
  • Riccardo Bovo
  • Manuel Fradinho Oliveira
  • Simon Julier

Institusjon(er)

  • SINTEF Digital / Teknologiledelse
  • University College London

År

2018

Publisert i

Lecture Notes in Computer Science (LNCS)

ISSN

0302-9743

Forlag

Springer

Årgang

11315

Side(r)

84 - 93

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