# A Scoping Review on Virtual Reality-Based Industrial Training
## 3 Results
### Literature Review
#### Industrial Training Based on Virtual Reality  
Industry 4.0, which is also known as the fourth industrial revolution, has grown exponentially in recent years, raising the level of development of technologies, such as VR, and allowing this type of digital tools to be used for training and creating qualified human resources. [PERSON] et al. [45] formulated a VR training prototype for assembly tasks. The main part of this study focuses on the fact that, within several previously programmed VR environments, an expert performs familiar works procedures. These actions are recorded to be reproduced in the next stage of the experiment. In phase two, an operator or professional without knowledge in the assembly area intervenes. Here, this user, called student, observes and follows the expert's recording step-by-step, giving an orientation of \"practical authorship\" to the research. This concept has great potential within industrial areas, such as (i) process planning, since, through remote inspection, it is possible to verify how the assembly procedures are being carried out, (ii) design reviews, to record, control, and care for the quality of the final product; and, (iii) maintenance, to keep a record of instructions for situations that are complex or very rare and, thus, avoid wasting human and economic resources. [PERSON] et al. [46] propose a low-cost architecture, which includes the use of virtual reality to control an industrial robot manipulator, in order to train operators in a fully immersive environment. The proposed environment was developed in Blender and it had the same characteristics as the real workstation. On the other hand, the human-machine interaction has been implemented through Unity 3D. The teleporting function has been used, so that the operator can move around and interact with the entire programmed environment. For validating this system, 12 people divided into three groups, (i) robotic application engineers, (ii) robot operators, and (iii) assistant operators. Twelve questions were applied and scored on the Likert scale. The results were encouraging; and, the participating professionals concluded that the integration of a training system, simulation and robotic control increased the efficiency in carrying out their tasks. A training system specifically designed for Industry 4.0 through the use of process mining and virtual reality is detailed by [PERSON], et al. [47]. The use of this system focuses on two groups of participants; the first centred on expert workers and second aimed at trainees or apprentices. The objective of this system is that expert workers, through an immersive interface, make assemblies that can vary, according to their experience. After this, improved assembly models are created through the application of algorithms for process mining. Apprentice operators use this information to train and get adequate feedback on their tasks. By applying the one-way ANOVA, it was found that immersive training is significantly better than conventional training in terms of performance, learning, results, and mental demand. [PERSON] et al. [48] introduce a virtual training platform for IMA (industrial maintenance and assembly) tasks. Additionally, they establish that to evaluate the operation of these systems; it is necessary to measure both their efficiency and effectiveness. In this way, forty expert technicians were randomly assigned to various training groups to carry out an electronic actuator assembly task. These groups were divided into four sections, (i) training with the virtual reality platform, (ii) see a demonstration of the filmed activity, (iii) training with the augmented reality platform, and (iv) training with the real actuator and guide of a video demonstration. The conclusions that were obtained from this study were encouraging for virtual platforms, since, despite requiring higher concentration, they allowed operators in order to develop their activities in a better way.