A taxonomy for combining activity recognition and process discovery in industrial environments

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

9 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning – IDEAL 2018 - 19th International Conference, Proceedings
EditorsDavid Camacho, Paulo Novais, Antonio J. Tallón-Ballesteros, Hujun Yin
PublisherSpringer
Pages84-93
Number of pages10
ISBN (Print)9783030034955
DOIs
Publication statusPublished - 2018
Externally publishedYes
Event19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018 - Madrid, Spain
Duration: 21 Nov 201823 Nov 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11315 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018
CountrySpain
CityMadrid
Period21/11/1823/11/18

Keywords

  • Activity recognition
  • Industrial environment
  • Literature overview
  • Manufacturing
  • Process mining
  • Tacit knowledge

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