Augmented Reality In The Manufacturing Industry – Just Hype Or Real Added Value?

Augmented Reality (AR) has long been a buzzword in the manufacturing industry, but technology is beginning to spread to the masses. A pretty surprising development. For a long time on the annual Gartner Hype Cycle, AR has remained on the descent into the valley of disappointments, while now it can be found on the so-called path to enlightenment. So what caused this trend reversal?

The worker stands in front of his object – for example, a car body. The tablet he’s carrying is connected to an application in the cloud that shows him instantly and precisely where he needs to rework. After the work is done, the visual display reports the result, and the worker can immediately move on to the next object. Such an idea was long considered science fiction, even if the technology was heavily hyped. Two hurdles, in particular, stood in the way of the mass dissemination of AR.

Tracking Technology: The traceability of the dynamic movements of the viewer and object was an enormous challenge for a long time. For example, when a car body moved down a production line, the technology struggled to keep up with the constant movement. This hurdle could be overcome with more powerful mobile devices and improved algorithms for markerless model-based tracking. Previously, continuous tracking breaks were expected when the component moved, but data can now be reliably projected onto mobile objects. This allows the worker to move freely around the thing with his tool.

Data Processes: The availability of 3D data is another essential requirement of AR. Due to technical limitations, however, many places were still drawn in 2D until a few years ago. In the meantime, the seamless construction of products in a 3D master has become widely accepted. In addition, production-relevant meta information such as dimensions or assemblies is stored in the 3D model as PMIs (Product Manufacturing Information). However, the processing and visualization of 3D data consume enormous computing power. With the advent of cloud-based technologies, heavy computational work can now be offloaded to the cloud. WLAN also allows it to visualize data anywhere on the shop floor dynamically. So can the results calculated in the cloud be streamed to the device via WLAN.

Also Read: What’s Next Step For Augmented Reality

The Foundation Of A Sustainable Manufacturing Industry

To remain globally competitive in the future, companies must produce as cost-efficiently as possible. At the same time, they face the challenge of mastering a growing number of variants and ever shorter product life cycles. A high degree of automation is required for the transformation to a sustainable Smart Factory to succeed.

However, manual activities will never completely disappear from the industry – whether in assembly, quality assurance, or rework. Therefore, linking analog processes with AR technology has become a business priority. Manual labor will continue to extend across all manufacturing industries and the production chain. Companies are confronted with a growing variety of variants. This means that jobs are becoming increasingly complex, making it difficult for workers to avoid or correct mistakes. The industry is therefore attaching increasing importance to technologies that digitally support workers in their work.

However, since it is not (yet) practicable to wear AR glasses for long periods, precise positioning cannot be implemented with them anyway. Because using a tablet hinders work, AR software for dynamic laser and video projection is a good idea. This helps the worker, for example, when attaching components. Based on 3D planning data, position data or assembly instructions can also be projected directly and precisely onto objects with complex shapes. Even if product lines and equipment variables change, the worker always knows at which positions he has to attach a component – the error rate and thus the costs drop enormously.

Based on 3D planning data, position data or assembly instructions can also be projected directly and precisely onto objects with complex shapes. Even if product lines and equipment variables change, the worker always knows at which positions he has to attach a component – the error rate and thus the costs drop enormously. Based on 3D planning data, position data or assembly instructions can also be projected directly and precisely onto objects with complex shapes. Even if product lines and equipment variables change, the worker always knows at which positions he has to attach a component – the error rate and thus the costs drop enormously.

Practical Example: AR At A Car Manufacturer

A large automobile manufacturer uses dynamic laser projection, including tool tracking, in the paint shop. Manual rework is necessary to ensure that the vehicle paintwork is flawless and does not show any signs of damage, such as dust inclusions or craters. In the finished cabin, employees look for the points to be reworked and correct them by hand. The car manufacturer is optimizing this process with AR technology. First, a vision system automatically and AI-supported identifies potential spots on the entire vehicle surface. Lasers then project their positions directly onto the cars in the downstream finish areas. Wherever the worker has to grind, he sees a green triangle.

The projection follows the body, even if it is lifted on a lifting table or moved along the line. While the employee lends a hand, the tool tracking automatically recognizes the current tool and how long it remains in the position. This way, it knows when the work step is done. The display changes and the laser projects a green circle instead of a triangle. This signals to the worker that he still has to polish here. When the entire process is complete, the display disappears entirely.

In this way, the employee can be sure that he has processed all the areas that need to be improved. If he discovers additional features in the paint that the image recognition has overlooked, he can enter them manually into the system using a handheld device on his wrist. They, too, are then transferred to the digital model. In addition, the tool tracking documents process parameters such as the processing time and the contact pressure during grinding and polishing. The car manufacturer collects and analyses all this data to optimize production further. This example impressively demonstrates how AR can now be used in the manufacturing industry to increase efficiency.

The Future Of AR

Augmented Reality has meanwhile made the leap from a promising prototype technology to mass application. AR-based technologies are no longer seen as science fiction but are now simple auxiliary tools in almost all industrial sectors. Currently, however, mainly corporations and larger medium-sized companies use AR. SMEs still face the challenge of creating interfaces for the technology and expanding their digital infrastructure. The more AR technologies spread and the lower the production costs; the more attractive AR becomes for SMEs.

After all, the possibilities of technology are far from being thoroughly exhausted. In the future, it is conceivable to use gesture control, image processing, and depth cameras to analyze process data during processing directly and automatically have it flow back into digital models. The vision of augmented Reality goes even further.

Also Read: Augmented Reality | Types, Characteristics, Advantages & Disadvantages Of AR

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