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

  • Felix Mannhardt
  • Riccardo Bovo
  • Manuel Fradinho Oliveira
  • Simon Julier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11315)

Abstract

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.

Keywords

Activity recognition Process mining Manufacturing Industrial environment Tacit knowledge Literature overview 

Notes

Acknowledgments

This research has received funding from the European Union’s H2020 research and innovation programme under grant agreement no. 723737 (HUMAN).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.SINTEF DigitalTrondheimNorway
  2. 2.Department of Computer ScienceUCLLondonUK

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