{"id":10543,"date":"2023-09-26T15:46:28","date_gmt":"2023-09-26T13:46:28","guid":{"rendered":"https:\/\/www.inpro.de\/main-topic-industrial-metaverse\/"},"modified":"2024-08-26T11:04:14","modified_gmt":"2024-08-26T09:04:14","slug":"main-topic-industrial-metaverse","status":"publish","type":"post","link":"https:\/\/www.inpro.de\/en\/main-topic-industrial-metaverse\/","title":{"rendered":"Industrial Metaverse: Technology, use cases and partnerships"},"content":{"rendered":"

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Industrial Metaverse<\/h1>

Technological building blocks, use cases and partnerships <\/p><\/div><\/div><\/div><\/div><\/div><\/div><\/div>

From Industry 4.0 to the Industrial Metaverse<\/h1><\/div><\/div><\/div><\/div><\/div>

The digitization of industry is advancing and new potential is constantly emerging through the use of innovative technologies such as artificial intelligence. The automation of production also continues to advance. However, the increasingly dynamic change in product requirements and technological possibilities also makes it necessary for production processes to be planned, modeled and implemented more quickly and with greater accuracy.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

The next evolutionary stage of digitization will be achieved through the networked virtual control and optimization of product development and production planning<\/a>. This requires an intelligent combination of a large number of existing and disruptive technologies with D\u00f6man knowledge, as well as entirely new forms of collaboration between engineers, data scientists, and employees and machines on the store floor.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

Networked virtualization of product development and production<\/p>\n

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New opportunities for holistic optimization are emerging through networked digital twins in integrative collaboration environments such as Nvidia’s Omniverse<\/a>. They are not only key to greater efficiency in product creation, but could also develop into the heart of the autonomous factory of the future.<\/p>\n

The digital twin is the virtual representation of a physical object that can be optimized and further developed along its entire life cycle using real-time data and simulations. As a result, prototype construction, for example, can be cost-effectively, almost completely virtualized, or the use of robots in manufacturing can be perfected to prevent accidents and damage in the trade. Virtualization of product development and production also increases the speed of innovation: New materials and manufacturing processes can be simulated and tested in their entire impact on the value chain. If entire teams can then work in parallel on their digital twins in a network without time-consuming data transfer, the result is a highly efficient, collaborative working environment. This is not only helpful in the design and control phase, but can also be put to good use during training and maintenance work on the machines.<\/p>\n<\/div><\/div><\/div><\/div><\/div>

Current challenges in the implementation of the Industrial Metaverse<\/h1><\/div>

According to a recent study by MIT<\/a>, the market potential of the Industrial Metaverse will increase tenfold to around USD 100 billion by 2030. In our consulting activities, we are also observing a strong interest in industrial metaverse applications and assume that many innovative technologies will pay off in combination to realize the industrial metaverse. We are at the beginning of a new production era. However, the first successful developments also highlight the challenges that currently need to be solved:<\/span><\/p>\n<\/div>

Identification of the use cases <\/h2><\/div>
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The full potential of the Industrial Metaverse only emerges from the synergetic networking of the many applications. This can make it difficult to present convincing economic analyses for individual use cases. The interdisciplinary nature of the complex of topics requires collaboration among subject matter experts who operate with different concepts and terms, which can make problem identification and a common understanding of solutions difficult. Specialized innovation consultants can build the necessary bridge of understanding and contribute their experience with pioneering work.<\/p>\n<\/div><\/div><\/div>

Capture and manage scan data <\/h2><\/div>
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A basic prerequisite for many industrial metaverse applications are networked multiphysical simulations that incorporate real data from the physical world. Despite enormous progress in data processing via innovative scanning devices and 3D scanners, the required degree of accuracy of data measurement is still often insufficient to date. Significant improvements must therefore be made in the acquisition and processing of measurement data and automatic quality mechanisms must be developed to enable the dynamic use of real data in virtual auxiliary worlds.<\/p>\n<\/div><\/div><\/div>

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Isolated solutions vs. complexity of the interplay of disruptive technologies<\/h2><\/div>
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The realization of the Industrial Metaverse requires new technologies, but these build on existing solutions. Process gaps will have to be closed with technological building blocks. The key to timely implementation success lies in powerful ecosystems that enable manufacturing companies to easily get started with Industrial Metaverse applications. Partnerships with digital innovation leaders such as Siemens and investments in the joint further development of the Industrial Metaverse are trend-setting in this respect, but also leave specialized solution providers sufficient scope to shape the topic area.<\/p>\n<\/div><\/div><\/div>

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