Execute virtual commissioning scenarios on a Manufacturing virtual twin including accurate simulation of Robots, equipment, and sensors connected to a PLC program
Robotics Virtual Commissioning Analyst (RVN) enables the execution of virtual commissioning scenarios based on the pre-defined 3D Virtual Twin. Multiple scenarios consist of tuning capabilities that adapt the sensor shape or position, or the ability to change part creation frequencies. Other scenarios include enabling virtual validation and correction of the PLC program to accelerate the start of production, reducing costly downtime by leveraging the virtual twin to train operators and maintenance workers, and predicting the workcell cycle time by connecting the virtual robot to the RRS II standard or any proprietary virtual robot controller servers.
When RVN is combined with any other Robotics simulation role (RSN, RBS, RSG, RFP, RAM), the user can create the virtual twin in the Robotics workcell by creating sensors, parts, logic, and tasks, then connect to CATIA ControlBuild with the associated mapping table.
Simulate Robots with a high level of accuracy
RVN provides virtual 3D simulation and validation of native language robot programs using the robot vendor’s Virtual Robot Controller (VRC) software, which implements the Realistic Robot Simulation II (RRS-II) interface standard. The virtual robot’s cycle time and trajectory can be simulated with nearly 100 percent accuracy compared to the physical robot. Users can also program and simulate a robot using a virtual teach pendant, when provided by the robot manufacturer that mimics the teach pendant used on the physical robot. RVN can be also independent of any other CATIA SYSTEM role, allowing users to run machines and/or robot simulations with all PLC emulators to validate the controls program.
Closely Integrated with CATIA Control Build
Robotics Virtual Commissioning Analyst (RVN) delivers an immersive 3D experience to virtually validate the PLC program of machines and/or robots in the factory context. RVN provides the connector that allows a close integration with CATIA ControlBuild where users can develop, integrate, and validate control systems for industrial automation.
RVN’s integration with CATIA ControlBuild provides high performance communication for virtual validation or with the real PLC (hardware in the loop) of the automation controls system.
Part creation and transformation
For multicycle simulations, you can generate the same parts, manage different transformations, and create & fill part attributes for use in the logic through the sensors.
RVN provides the user with the capabilities to model different type of sensors for virtual commissioning. Each sensor has a physical component as well as a behavior model. When used in the simulation, the individual behavior of the sensor (such as sending an output when physical contact is made) allows the user to detect the presence of parts in the zone detection, allowing input and output PLC - SIMULATION interaction.
These sensors can detect any 3D object in their detection zone and set an output signal used in the task or in a program to simulate a line or work cell behavior. They can also read the detected part’s attribute value established by the source command and sets the sensor outputs accordingly. It allows for multiple simulation scenarios.
Different types of sensor are available: 1D as a beam, 2D as a plan, and 3D as a volume. On each sensor, different zone detections with different output set-ups can be created.
RVN offers different types of connectors:
- OPC (open platform communication) to control simulations with PLC ladder logic
- FMU (functional Mock-up interface)
- OPC UA is also available through CATIA Control Build
Virtual teach pendant
Thanks to the RRS II and the robot vendor’s Virtual Robot Controller (VRC) software connector, Expert users can program and simulate a robot using a virtual teach pendant, when provided by the robot manufacturer that mimics the teach pendant used on the physical robot. This allows Robot Programmers familiar with the physical hardware to quickly program robot-specific instructions.
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