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Using a game-based learning approach in teaching overall equipment effectiveness
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Volvo Construction Equipment, Eskilstuna, Sweden.ORCID iD: 0000-0002-0729-0122
2020 (English)In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 26, no 3, p. 489-507Article in journal (Refereed) Published
Abstract [en]

Purpose – The purpose of this paper is to develop a novel training material for the performance indicator overall equipment effectiveness (OEE) in the form of a game-based learning (GBL) approach to be used in Industry and University context. The paper will present the development of the game as well as results from tests of the game with Industry employees and University students. Design/methodology/approach – The data that are used in the game have been acquired from real OEE data logs of a reference company. The game has been refined iteratively using feedback from the participants of the tests. Findings – The paper presents the game with its components and learning objectives. A comparison of various theoretical factors on GBL and the novel trainingmaterial is performed and future improvements are suggested. Research limitations/implications – The game has been developed based on OEE data logs from only one reference company. Practical implications – The training material and specifically the game can be used to train Industrial workers and University students to better envision OEE as a performance indicator. Originality/value – Serious games on lean manufacturing have been developed and played for a long time. While some of these games include OEE as an important result parameter, none really demonstrates how it is measured and analyzed.

Place, publisher, year, edition, pages
2020. Vol. 26, no 3, p. 489-507
Keywords [en]
Performance measurement, Training, Lean manufacturing, Game-based learning, Overall equipment effectiveness
National Category
Engineering and Technology Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:mdh:diva-46275DOI: 10.1108/JQME-03-2019-0031ISI: 000546970600007Scopus ID: 2-s2.0-85075082107OAI: oai:DiVA.org:mdh-46275DiVA, id: diva2:1376900
Projects
XPRES - Excellence in Production ResearchAvailable from: 2019-12-10 Created: 2019-12-10 Last updated: 2020-10-07Bibliographically approved

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Bengtsson, Marcus

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