Training Operator in VR: A Scalable Solution for the Creation of VR Training Scenes
Paper in proceeding, 2025

In the automotive industry, just like in other complex product-based industries, fierce competition is ongoing, and companies must cope with the challenges. In such industries, operator training is a cornerstone, as many of the most important product manufacturing processes rely on human-performed assembly. Thus, with the factory environments that are getting increasingly complex, and efficiency-dedicated, the importance of training is enhanced. With the generalization of Virtual Reality (VR) technologies, VR operator training emerges more rapidly. However, the many advantages of VR training, such as safety, cost, and flexibility, have not yet been fully realized in the industry as large-scale implementations still have not been reached. Creating VR training scenes is still time-consuming, and therefore expensive, hindering large-scale implementation and adaptation. This paper first recapitulates the data needed to populate such VR training scenes, then it exemplifies the automatic generation of VR training scenes through an industry use case, enabling large-scale automated implementation. Finally, it highlights the challenges related to data availability and handling and that companies can encounter on the way to the large-scale implementation of VR training.

Scalable

Training

Automated

Operator 5.0

IPS

PLM

Assembly

Virtual reality

Author

Geoffrey Melzani

Student at Chalmers

Tony Quach

Student at Chalmers

Henrik Söderlund

Chalmers, Industrial and Materials Science, Production Systems

Dan Li

Volvo Group

Puranjay Mugur

Volvo Group

Björn Johansson

Chalmers, Industrial and Materials Science, Production Systems

Communications in Computer and Information Science

1865-0929 (ISSN) 18650937 (eISSN)

Vol. 2373 CCIS 332-342
9783031807749 (ISBN)

5th International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2024
Porto, Portugal,

PLENary multi-User developMent arena for industrial workspaces (PLENUM)

VINNOVA (2022-01704), 2022-09-15 -- 2025-09-14.

Subject Categories (SSIF 2025)

Production Engineering, Human Work Science and Ergonomics

Computer Systems

Areas of Advance

Production

DOI

10.1007/978-3-031-80775-6_23

ISBN

9783031807749

More information

Latest update

3/12/2025