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

Mannhardt, F; Bovo, R; Oliveira, MF; Julier, S; (2018) A taxonomy for combining activity recognition and process discovery in industrial environments. In: 19th International Conference, Madrid, Spain, November 21–23, 2018, Proceedings, Part I. (pp. pp. 84-93). Springer: Madrid, Spain. Green open access

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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.

Type: Proceedings paper
Title: A taxonomy for combining activity recognition and process discovery in industrial environments
Event: Intelligent Data Engineering and Automated Learning – IDEAL 2018
Location: Madrid, Spain
Dates: 21–23, November, 2018,
ISBN-13: 9783030034955
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-03496-2_10
Publisher version: https://doi.org/10.1007/978-3-030-03496-2_10
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Activity recognition · Process mining · Manufacturing · Industrial environment · Tacit knowledge · Literature overview.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10070701
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