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.