JUNE 2025
From Simulation to Reality:
How Digital Twins Improve
Robotic Welding Efficiency
Digital twins are transforming industrial manufacturing by bridging the gap between virtual simulation and real-world execution. In robotic welding, digital modeling technology allows engineers to virtually plan, optimize, and validate the entire welding process before the robot performs it on the actual workpiece.
This approach minimizes setup time and reduces the risk of errors—all while providing a scalable framework for complex production tasks.
This approach minimizes setup time and reduces the risk of errors—all while providing a scalable framework for complex production tasks.
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What Is a Digital Twin (and Why Should You Care)?
A digital twin is a virtual replica of a physical object or system. In our case, that means a fully modeled 3D environment of the robotic welding cell— complete with geometry, motion constraints, and even the specific workpiece to be welded. But this isn’t just a pretty picture. It’s an active simulation environment where welding paths are calculated, errors are identified before they occur, and production steps are validated virtually before any real-world action is taken.
A digital twin is a virtual replica of a physical object or system. In our case, that means a fully modeled 3D environment of the robotic welding cell— complete with geometry, motion constraints, and even the specific workpiece to be welded. But this isn’t just a pretty picture. It’s an active simulation environment where welding paths are calculated, errors are identified before they occur, and production steps are validated virtually before any real-world action is taken.
Creating a Robotic Welding Digital Twin
Before any welding begins, the robotic welding cell layout is captured digitally for simulation. This includes positions and dimensions of key elements such as the robot arm, welding equipment, track, positioner, cleaning station and 3D scanners. This digital model forms the basis for subsequent simulation and trajectory planning.
The digital twin of the cell is created manually in CAD-like engineering software. Configurations, geometries, and constraints are defined by engineers and designers in advance. This model is then imported into the system, where it becomes the foundation for simulation. This virtual replica accounts for both the static environment and the dynamic
behavior of the robotic arm, including its kinematic constraints and safety boundaries.
Simulation pre-generates collision-free trajectories and optimizes them for maximum efficiency. It also enables the identification of unreachable zones or suboptimal tool paths before they can affect real-world operations.In some cases, scanning also reveals assembly errors in the parts themselves, such as misplaced holes or incorrect plate positions that don’t match the original design drawings. This early detection prevents defects from propagating downstream.
The digital twin of the cell is created manually in CAD-like engineering software. Configurations, geometries, and constraints are defined by engineers and designers in advance. This model is then imported into the system, where it becomes the foundation for simulation. This virtual replica accounts for both the static environment and the dynamic
behavior of the robotic arm, including its kinematic constraints and safety boundaries.
Simulation pre-generates collision-free trajectories and optimizes them for maximum efficiency. It also enables the identification of unreachable zones or suboptimal tool paths before they can affect real-world operations.In some cases, scanning also reveals assembly errors in the parts themselves, such as misplaced holes or incorrect plate positions that don’t match the original design drawings. This early detection prevents defects from propagating downstream.
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In most real-world scenarios, this preparatory work is handled by system integrators or automation providers. This means that companies don’t need to have in-house experts in robotics, 3D modeling, or simulation. Integrators take on the heavy lifting—setting up the environment, verifying configurations, and preparing the system for use—so that customers can access advanced automation with minimal technical overhead.
Integrating the Workpiece
During scanning, the system searches for a real-world object that matches the engineer’s 3D model of the workpiece. Once a match is found, the digital model is automatically positioned inside the digital twin of the cell to reflect the workpiece’s actual location in the physical environment. For demonstration purposes, a mini-beam part is used—a compact but geometrically relevant example.
The part is scanned directly in its installed position to determine its exact location and orientation within the cell. Once this is established, weld joint scanning is performed before welding each seam to capture the precise geometry of the weld joints, ensuring even greater accuracy. This sequence ensures that the virtual simulation environment is aligned with real-world conditions and that welding paths are generated with high accuracy.
The part is scanned directly in its installed position to determine its exact location and orientation within the cell. Once this is established, weld joint scanning is performed before welding each seam to capture the precise geometry of the weld joints, ensuring even greater accuracy. This sequence ensures that the virtual simulation environment is aligned with real-world conditions and that welding paths are generated with high accuracy.
Virtual Weld Planning
and Robot Trajectory Generation
With both the cell and the part modeled in software, the next stage is task definition by the engineer. This includes specifying weld seams and assigning parameters such as orientation of the tool and welding speed for each seam. The system then takes over the complex part: it generates precise robot trajectories and machine commands based on this input. This division of responsibility allows users to focus on defining the welding intent, while the system handles collision-free generation, motion planning, and equipment control.
Executing Robotic Welds in Reality
Once the simulated process is verified, the robot does not immediately begin welding. Before executing each seam, the system scans the corresponding weld zone to account for deformation. This step ensures that any deformations or misalignments that may have occurred—particularly as a result of previous welds—are accounted for. Instead of scanning all seams at once, scanning is done progressively to handle the cumulative effects of thermal deformation and ensure high accuracy throughout the entire welding process.
This method eliminates the need for manual programming and dry-runs—saving time and reducing production downtime.
This method eliminates the need for manual programming and dry-runs—saving time and reducing production downtime.
Key Benefits of Digital Twin Simulation
in Robotic Welding
- Reduced setup time: Physical trial-and-error is eliminated through virtual validation.
- Improved quality: Robotic welding paths can be optimized for any parts and cell layouts.
- Operational flexibility: The digital twin-based robotic welding system can quickly adapt to part deviations or production changes.
- Increased safety: Simulation helps avoid collisions and misuse of tools. Scanning also reveals assembly errors in the parts themselves, such as misplaced holes or incorrect plate positions that don’t match the original design drawings.
As digital modeling evolves, its role in robotic manufacturing continues to grow—enabling more intelligent, automated, and adaptive production environments.
Frequently Asked Questions (FAQ)
A digital twin is a virtual replica of a welding cell and its components, including the robot, positioner, and workpiece. It allows for simulation, planning, and error detection before real- world execution.
Simulation helps pre-generate collision-free trajectories, verify reachability, and catch potential errors or misalignments early—saving time and reducing waste.
Digital twins provide a close approximation, but real-world accuracy is improved by scanning each seam before welding to account for deformation and build-up of error during production.
No. Integrators handle the technical setup, so end-users don’t need deep knowledge in CAD or robotics. The system is designed to be accessible and easy to operate after deployment.
Yes. Scanning often reveals mismatches between design and reality—such as misplaced holes or incorrectly assembled components—which can be corrected before welding begins.
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