How can AR technology be applied on a large scale in the industrial field, and what bottlenecks in technology development need to be broken through?
For industrial enterprises, what is the biggest difficulty in deploying AR applications, and what are the difficulties in landing them?
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On June 30th, with the theme of "How AR Helps the Industrial 'Universe'", Tiger Sniff held the "502 Online Peers" AR special event on industrial digital transformation. ALVA Systems was invited as an industrial AR application expert to participate in the conference . End-user companies in the field of industrial manufacturing discussed the topic of industrial AR application landing. Many companies raised many specific bottlenecks and concerns in the deployment process on the premise of clarifying the important development trend of industrial AR applications.
The evolution and development of innovative technologies need to go through continuous practice and dialectics in the market. Today, we will use the views and opinions of some users in the conference to talk to you about the current dilemma and problems of industrial AR deployment.
AR applications locked in the "display" layer
"In many application cases, such as detection and monitoring, data calculation itself is completed by existing systems. What other functions does AR have besides display?"
Many manufacturing companies' perception of the value of AR applications is more at the "display" level. It is true that visualization is the most direct application value of AR, and it is relatively more mature in specific applications. Judging from the existing implementation cases of ALVA , the application of AR display type has been widely used in the visual display of data information, structural components, technical principles and other levels of equipment, which is the "icing on the cake" of the traditional method.
But it should not be limited to "display". "Enterprises' understanding of the role of AR should transition from the three technical advantages of visualization, instruction guidance, and interaction to data access, data enhancement, and the application value of digitization of human behavior . "Guo Junxi, Product Planning Director of ALVA Systems, said in the meeting.
We might as well understand this point of view in conjunction with the next question: "If you want to build enterprise digital assets and knowledge graphs through AR technology, do you rely on videos specifically? Are there other forms?"
In fact, shooting operation videos through MR glasses only completes the [acquisition] action of knowledge and skill assets, and more value of AR applications is reflected in the sorting out and reuse of workflows.
The workflow and operation steps collected by MR glasses need to be further integrated to highlight key information and form reusable technical resources or training courses.
Junior engineers can directly conduct course learning, training and assessment through the platform, forming a value closed loop of knowledge and skill accumulation, reuse, optimization and update.
Based on this application scenario, ALVA Expert Guider can provide a complete knowledge and experience reuse platform for industrial manufacturing enterprises with different capabilities and resources, copy the workflow digital experience of leading enterprises with one click, and form a suitable Self-developed knowledge base.
Moreover, the content of the experience library is not limited to video content. Enterprises can use digital twins of products, equipment and even factories to create more and more intuitive AR application courses and more standardized workflows. However, in this process, the implementation of When it comes to specific operations, many users said that there is a bottleneck problem in the production of AR content.
Insurmountable AR Content Production Bottleneck
As we previously shared in the article " Expert Science|Soldiers and horses have not moved, food and grass first, what did the 3D assembly line do before AR/VR applications? " Steps, companies need to solve not only the problem of AR development, even for companies with ready-made models, there is a long distance from solid models to cool dynamic special effects, excellent display effects and excellent application experience for those without relevant professional It is difficult for traditional industrial manufacturing enterprises with technical personnel.
In the face of development problems, ALVA has been able to provide industrial manufacturing enterprises with an out-of-the-box content editing and creation platform - ALVA Editor. From model creation, production to release, it only takes three simple steps.
With a wealth of special effects and material templates, ALVA Editor can meet basic content production requirements. It has been able to do a job well in the production of training guidance courses, AR manuals, and operation manuals. In the project, most client companies also need to rely on ALVA's professional content production team to meet higher requirements for content production.
In this regard, we are also continuously optimizing at the product level to meet higher requirements through more abundant resources. At the same time, we have also found that many companies that intend to deploy the metaverse track have realized the importance of content production and are focusing on cultivating relevant talents, so as to produce more professional and differentiated content for enterprises.
In this event, we found that many industrial manufacturing companies already have a relatively clear understanding of AR applications, but they have many doubts and concerns about the specific application value.
In this regard, Guo Junxi also made suggestions for industrial manufacturing companies: "From small AR to large space interaction, enterprises should jump out of technology and look at industrial application models, focusing on data resources, data analysis, and the value transformation of knowledge and experience." In the specific implementation , He pointed out: "Before deployment, enterprises should take high-frequency and simple requirements as daily applications for fast and lightweight deployment according to application scenarios, and low-frequency and core scenarios as key and long-term deployments."
Back to the theme of the event, compared with the broad concept of "metaverse", the industrial metaverse is already quite concrete. Faced with a more standardized industrial manufacturing scene, the metaverse is more hopeful that it will be implemented quickly, and it is not limited to conventional AR application scenarios , in our continuous cooperation with customers, we have also explored many new application directions and ideas.
What do you think of the landing of AR in the field of industrial manufacturing? Welcome to leave a message to exchange!
About ALVA Systems
ALVA Systems is the world's leading provider of software and hardware for heterogeneous computing technology. Together with the National Institute of Metrology of China, it designed the world's first benchmarking tool for heterogeneous computing technology and improved its CPU and GPU hardware for AMD, Intel, Qualcomm, and ARM. Design and underlying driver function library to better adapt to heterogeneous computing.
In recent years, ALVA has applied its leading technology advantages in the field of heterogeneous computing to the field of industrial Internet of Things. The advanced underlying heterogeneous computing technology allows ALVA to provide users with excellent and high-efficiency AR experience in low-latency scenarios. ALVA Systems leads the market demand with technological innovation and is committed to becoming your source of innovation.