"Creating virtual cases through digital twins is essential to overcome data collection limitations in the AI-powered autonomous phase of digital transformation."

Hexagon held the 'HEXAGON Live Innovation Summit Korea 2025' at the AT Center in Seoul on the 3rd.

At the event, Hong Seok-kwan, President of Hexagon Manufacturing Intelligence's Metrology Division, presented on the topic of "Smart Manufacturing Completed with Hexagon Data," explaining the key relationship between digital transformation (DX) and autonomy (AX) in the manufacturing industry and suggesting a realistic approach.

CEO Hong Seok-kwan pointed out that while the digital transformation phase is already being applied to manufacturing sites, the limitations of data collection remain the biggest challenge in the AI-powered autonomous phase.

Optimizing a robot program requires thousands to tens of thousands of simulation data, but securing the raw data required in actual fields is not easy.

To overcome thisHe emphasized that creating virtual cases through digital twins is essential.

He explained that to maximize the effect, it is necessary to prioritize application in four areas, including equipment predictive maintenance, quality management, demand forecasting, and cycle time reduction, which are particularly important from an ROI perspective.

He suggested that we should start with the digitalization of production resources, and move on to optimization using simulation and real-time control, and innovation through the application of AI.

In the metrology space, Hexagon introduced wideband 3D scanners and ultra-precision measuring equipment.

The company announced that it will provide solutions that can be used for reverse engineering and quality inspection with precision of less than 10μm for product units, while long-range scanners can be used for large-scale environments such as factories, bridges, and cities.

This allows the process to be converted into a CAD model and, if necessary, combined with CAS analysis to optimize the design and air conditioning system.

To implement industrial robot autonomy, a calibration process is required to match the attribute information of the virtual robot and the actual robot.

Hexagon uses a 3D measuring device to complement the robot's structural and joint characteristics in real time, and applies technology to reduce errors of hundreds of μm to tens of μm or less.

This enables automatic generation of predictable programs with an accuracy of less than 0.5 mm in robot-based additive manufacturing and painting processes.

At the heart of digital transformation is data sharing and collaboration.

Hexagon has created an environment where CAD-format drawings can be converted into various design software in a lightweight manner and drawing review history and changes can be managed in real time through its cloud-based collaboration platform, Nexus.

Starting this year, we will target shipbuilding equipment suppliers.The pilot project was launched, and the scope of collaboration is expected to expand to include CAE analysis and MRO (maintenance, repair and operation).

Hexagon has announced its intention to fully realize autonomous driving by introducing its humanoid robot, ‘Yeon’, to the European market.

Yeon has increased its operating rate with its own replaceable battery system, and combines multiple sensors such as lidar, stereo cameras, and width sensors to link reality capture and inspection functions with AI-based software.

CEO Hong emphasized, “Software-defined factories, which go beyond the automation stage of smart factories, aim for AI-decision-driven autonomy,” and “We cannot enter the AX stage without completing DX and digital twins.”

Mr. Hong also said, "Manufacturing sites are filled with complex challenges, but by clearly distinguishing the areas of application for each stage, we can accelerate innovation."