Efficient creation of a digital twin using AI methods
The full automated Toolchain from 360° Camera to simulation for digital twin generation
The use of a digital twin in the production process will be used, for example, for proactive planning, analysis of existing systems or process-parallel monitoring. Many companies, especially small and medium-sized enterprises, use the technology incorrectly or not. From your point of view, the generation of a digital twin is cost-, time- and resource-intensive. With our approach, these obstacles can be overcome quickly and easily, and the production layout and production logic (e.g. machine types, etc.) can be captured with a 360° Camera. The identification of CAD models and the transfer of geometric and other object data (e.g. machine types) from a reference library significantly reduces the recording of production. With the recognized machines, their properties are also known. With the comparison of the future production program, any simulation of the production can be created. Especially in the planning phase for investments, well-founded results based on a simulation model are indispensable for a target-oriented decision in today's world. In the presentation we will show you the procedure from scanning, object recognition to simulation and its challenges out of the way.
The full automated Toolchain from 360° Camera to simulation for digital twin generation
The use of a digital twin in the production process will be used, for example, for proactive planning, analysis of existing systems or process-parallel monitoring. Many companies, especially small and medium-sized enterprises, use the technology incorrectly or not. From your point of view, the generation of a digital twin is cost-, time- and resource-intensive. With our approach, these obstacles can be overcome quickly and easily, and the production layout and production logic (e.g. machine types, etc.) can be captured with a 360° Camera. The identification of CAD models and the transfer of geometric and other object data (e.g. machine types) from a reference library significantly reduces the recording of production. With the recognized machines, their properties are also known. With the comparison of the future production program, any simulation of the production can be created. Especially in the planning phase for investments, well-founded results based on a simulation model are indispensable for a target-oriented decision in today’s world. In the presentation we will show you the procedure from scanning, object recognition to simulation and its challenges out of the way.
