Customer Success Stories

VR training at Gerflor: “We can now do in a few hours what used to take six weeks”

At Gerflor, training an operator can take months of ‘shadowing’ on the job. Rémi Bousquet, Project Manager for Processes, explains how virtual reality, implemented in partnership with Inetum, optimises this training process without replacing human staff.

Gerflor, a specialist in floor coverings, operates two French factories, in Tarare (Rhône) and near Montélimar, each employing around 800 people. Training an operator there is a lengthy and costly process. As Methods Project Manager, Rémi Bousquet led a virtual reality training project with Inetum: a proof of concept by the end of 2024, followed by seven scenarios to be delivered in March 2026. He reflects on what works, what doesn’t, and why the machine has not replaced the trainer.

Published: 04/08/2026

What issue were you trying to address with regard to training?

Rémi Bousquet: To train our operators, we rely on mentoring: new recruits are paired with an experienced colleague. This lasts between one and six months, depending on the role. However, pairing means two people are tied up, and the learning process is uneven, depending as much on the mentor as on the mentee.

« Some of our scenarios replicate potentially dangerous situations, which we can re-enact without ever creating any real risk. »

Why did you choose virtual reality rather than augmented reality?

Rémi Bousquet: We’d tested augmented reality in 2022–2023 for maintenance purposes, but weren’t convinced. In 2024, I met Inetum at an immersive technology trade fair in Lyon. Their fully immersive simulation of work on the production line was enough to really capture my imagination. What I was looking for was simple to explain: a headset, a simulation, a scenario to follow – all carried out on-site. Above all, virtual reality allows the operator to be removed from the production line. Some of our scenarios replicate potentially dangerous situations, which we can replay as many times as necessary without ever creating any real risk. Augmented reality, on the other hand, does not allow for this.

Elian Cocchi, Innovation Engineer and 3D & AI Project Manager at Inetum

“One of the keys to success lies in the software we’ve developed in-house at Inetum, but also in the transparency of our collaboration with the client. On a day-to-day basis, whenever we had a question, we were able to liaise directly with the teams at Gerflor and move forward step by step, with the product being validated throughout its design process. The technology is now stable and will enable us to take bespoke solutions even further.

But behind the technology lies, above all, a business reality: enabling teams to save time and train in complete safety. In a simulation, an operational error poses no danger to the operator and results in no loss of production. That is the whole point of virtual reality: to replicate real-life situations, whilst eliminating risks and making the exercises repeatable as often as required.

This approach extends far beyond the industrial sector alone. For example, we work with schools that need to train their students in the detection of defects or pathologies.

In reality, it is not always possible to have the cases needed for learning to hand. In virtual reality, dozens of scenarios can be created and replayed as many times as necessary, without having to travel. Teachers can tailor the exercises to their needs and revisit a case with a pupil who has failed, until the procedure or diagnosis is mastered.

In the future, artificial intelligence will be able to further enhance these 3D environments, for example by incorporating characters capable of interacting realistically with the learner.”

Is everything suitable for VR?

Rémi Bousquet: No, and that’s the lesson we learnt from the first test project – the response to a production incident. There were too many nuances; each driver reacted in their own way depending on the severity of the situation. Yet a virtual reality scenario remains linear. It’s like a GRCET, really – that diagram that describes a procedure step by step. It’s difficult to fit such a complex tree structure with so many possibilities into that. A sequential scenario works much better: starting up a machine, shutting it down – a sequence of actions that’s identical regardless of the operator, and, above all, rare in real life. A production line start-up might happen once a week; if we consider that you need to have experienced it ten times to validate your competence, the training stretches over ten weeks.

How can the immersion be so accurate?

Rémi Bousquet: We’re lucky enough to have a sort of Google Street View of the factory, captured using a 3D camera. Inetum used this as a basis: using a point cloud, their teams took the exact measurements of the workstation without us having to take a single measurement ourselves. The result is accurate in terms of dimensions – which is the main thing – and in terms of textures, even if it doesn’t quite achieve photorealism. All the testers were immediately able to picture themselves in the environment: they know where they are and where they’re going.

Interaction is via joysticks. When several options are available, a decision tree is displayed: the correct answer turns green, the incorrect one red. We allow for mistakes, but immediately explain what the consequences would be for the machine.

« Information is retained much better than with a paper-based procedure.”

In practical terms, how does a training course work?

Rémi Bousquet: The role in question now has its own virtual reality module as part of the training programme. We don’t start with that: the new recruit first spends a week or two shadowing, to familiarise themselves with the production line. Next comes the headset, for a maximum of one hour per session. Any longer than that, even without nausea, fatigue sets in. We therefore stick to two one-hour sessions per week, over three to four weeks.

The operator is never alone. We support them as a team of three: the operator themselves, their mentor or a training specialist for technical queries, and a member of the training department to operate the equipment. The machine does not replace the human, but it allows us to practise and repeat tasks much more easily than on a production line.

What results did you measure?

Rémi Bousquet: At the end of 2025, we had 30 or 40 people test the headset, including operators from other workshops. The feedback was very positive regarding immersion and, above all, retention: information is retained much better than with a paper-based procedure. One work-study student even compared the two methods in her dissertation, using standardised tests. The results are clear: faster skills development, fewer repetitions required, and better retention, as the person is able to explain the ‘whys’ and ‘hows’.

Our aim is to reduce duplication time by 30 to 50 per cent, by condensing into two hours the procedures we previously repeated over six weeks. That said, nothing can replace the real thing: no one comes out of it capable of operating the machine on their own. But we are significantly speeding up the skills development process.

How have your teams reacted?

Rémi Bousquet: At the end of 2025, we had 30 or 40 people test the headset, including operators from other workshops. The feedback was very positive regarding immersion and, above all, retention: information is retained much better than with a paper-based procedure. One work-study student even compared the two methods in her dissertation, using standardised tests. The results are clear: faster skills development, fewer repetitions required, and better retention, as the person is able to explain the ‘whys’ and ‘hows’.