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An experimental study of the impact of virtual reality training on manufacturing operators on industrial robotic tasks
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Digital Smart Production.ORCID iD: 0000-0003-2993-511X
SnT, University of Luxembourg, Luxembourg.ORCID iD: 0000-0001-6064-5634
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0002-0723-1712
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2022 (English)In: Procedia CIRP, Elsevier BV , 2022, Vol. 106, p. 33-38Conference paper, Published paper (Refereed)
Abstract [en]

Despite the recent increase in Virtual Reality (VR) technologies employed for training manufacturing operators on industrial robotic tasks, the impact of VR methods compared to traditional ones is still unclear. This paper presents an experimental comparison of the two training approaches, with novice operators performing the same manufacturing tasks with a VR robot and with a real robot. The hardware selected is an ABB IRB 120 industrial robot, a HTC Vive head mounted display to operate it, besides a corresponding VR model developed in Unity. Twenty-four students performed two actions — drawing and “pick and place” -– in tasks with increasing difficulty, with both the VR model and the real robot. Completion time and task pass rate are adopted to estimate the learning efficiency, while a questionnaire evaluates the users’ satisfaction. The results show that students using VR overall need less elapsed time to complete all tasks, and they record a higher pass rate. The questionnaire answers show that 83% of participants find the VR model helpful in familiarizing with the real robot, and 75% are in favor of using the virtual tool for training novice operators. Users also report that moving the real robot is more complex than the virtual one; adjusting the speed is harder and the possibility of causing damage is worrisome, whereas the VR robot feels safer to operate and easier to drive. The majority of students are satisfied with the design of the tasks, and feel content with the experience. The main finding is that learning from a VR model allows to master driving a real robot quickly and easily. VR training is more useful than conventional methods because it reduces the learning time, allows for training without hindering production, lowers the risk perception, and improves safety for operators and industrial equipment.

Place, publisher, year, edition, pages
Elsevier BV , 2022. Vol. 106, p. 33-38
National Category
Robotics and automation Human Computer Interaction Computer and Information Sciences Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-321447DOI: 10.1016/j.procir.2022.02.151ISI: 001490148000006Scopus ID: 2-s2.0-85127464306OAI: oai:DiVA.org:kth-321447DiVA, id: diva2:1710922
Conference
9th CIRP Conference on Assembly Technology and Systems, CATS 2022, KU Leuven, 6-8 April 2022
Note

QC 20221116

Available from: 2022-11-15 Created: 2022-11-15 Last updated: 2025-12-05Bibliographically approved

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Publisher's full textScopushttps://www.sciencedirect.com/science/article/pii/S2212827122001524

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Monetti, Fabio Marcode Giorgio, AndreaYu, HaishengMaffei, AntonioRomero, Mario

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CiteExportLink to record
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