Could Augmented Reality (AR) be effectively introduced in the industry to support tasks such as maintenance, training, user manuals, collaborative design, and factory automation?
Various research suggests that AR has been adopted in an industrial environment to support maintenance. The superimposition of virtual models to complex products can help detect the correct part to operate on. On the other hand, enriching the real scene with writing and animations showing assembly/disassembly procedures can be useful to solve complex engineering problems by unskilled operators.
AR can be useful to reduce the complexity of user/maintenance manuals as well. In this case, instead of pages and pages of small complex drawings that are often unclear or hard to detect, contact with the real world can be useful to spare time and increase the process efficiency.
Maintenance training could take advantage of AR, where operators can be trained to operate on a real machine by acting on a virtual model so that there is no need to be in front of the object to familiarise, and eventual errors do not lead to damages. Remote collaboration capabilities have been proposed where a remote maintenance centre can guide an operator in complex tasks by preparing the required animations to support him/her in the work on the field.
Pick by vision is another interesting concept addressed to guide operators in selecting items to pick up in assembly tasks or logistics. The AR can be used to project a “virtual eye bull” or a “tunnel” to guide the operator towards the component to select. The industrial environment is particularly advantageous for AR since many highly detectable symbols lie in the factory and can be used as a marker.
As a result, thanks to AR, it is no longer necessary for the physical presence of the instructor where and when a training session is performed.
The hardware and software necessary to implement it depend on the internal/external application, the virtual scene’s complexity, the device held by the user, real-time, and the definition required by the application. However, the minimum hardware required to run AR application is given by a camera framing the external world, a screen, or a lens to project a video streaming, and the computational resources (PC, smartphone processor, microcontroller) necessary to handle the video recording, the pose detection and the superimposition of the visual symbols to it.
In industrial application, it is quite ambitious to say that AR rather than VR is a ready-to-use technology for factory applications because there are many difficulties to deal with, such as preparing the animations for all the possible tasks for operators. However, researchers believe that basic steps for a real industrial application are the creation of a 3D parametric CAD model, the exportation of these models in a mesh, simplifying the geometries tool, and the importation in Unity, where it is then possible to start scripting Augmented Reality for the final scene.
Bridging the Gap between AR and Industry Needs
Effective and efficient exploitation of AR capabilities in the industrial environment will be possible once a full Reality-Virtuality continuum is implemented. This concept, introduced by Paul Milgram, implies going beyond the distinction between Reality and Virtuality and presents for the user the capability to set the level of Virtuality he/she wants to work with in a simple way.
In AR industrial application, most importantly, the capability to mix Reality and Virtuality and switch between them simply, under the complete control of the operator who should be able to decide to stress the attention on virtual or real depending on the task they have to carry out.
Shadows, occlusion implemented in an effective way, rendered virtual models, high capability human-machine interfaces are some of the technologies which should be made available to users to overcome the distinction between real and virtual.
This article is adapted from Augmented Reality in Industry 4.0 and Future Innovation Programs. Technologies. 2021; 9(2):33 by Santi GM, Ceruti A, Liverani A, Osti F. https://doi.org/10.3390/technologies9020033
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