Virtual commissioning of robotic cells improves productivity by 15%

Why It Matters

This approach enables designers and engineers to identify and resolve control logic issues and optimize system performance in a virtual environment, reducing costly physical prototyping and commissioning time. It facilitates a more robust and efficient design process for complex automated systems.

Key Finding

By simulating robotic cells with integrated virtual robot and PLC controllers, designers can test and refine control logic to improve overall productivity before physical setup.

Key Findings

• The integrated virtual commissioning tool enables the simulation of complete robotic cell behavior.
• Control logic effects on overall productivity can be assessed and optimized in a virtual environment.
• The proposed method demonstrated feasibility and effectiveness in optimizing the final performance of a robotic assembly cell.

Research Evidence

Aim: How can virtual commissioning of robotic cells, integrating virtual robot and PLC controllers, be effectively implemented to verify and optimize control logic and overall system performance?

Method: Simulation and Virtual Prototyping

Procedure: A method was developed to integrate ABB RobotStudio with a Beckhoff PLC environment (TwinCAT) using a PLC Smart Component. This allowed for the execution of real robot control code on a virtual controller, synchronized with the PLC. The integrated system was then used to simulate and evaluate the performance of a robotic assembly cell.

Context: Robotic manufacturing cells, industrial automation

Design Principle

Validate and optimize complex automated system control logic through integrated virtual simulation prior to physical implementation.

How to Apply

When designing or modifying automated robotic systems, utilize simulation software that allows for the integration of both robot controllers and PLC logic to test and refine the control sequences and assess their impact on cycle times and error rates.

Limitations

The effectiveness may depend on the fidelity of the virtual models and the specific software tools used. Complex real-world environmental factors not simulated could still impact performance.

Student Guide (IB Design Technology)

Simple Explanation: You can test your robot and its control system (like a PLC) on a computer before building the real thing. This helps you find problems and make it work better and faster.

Why This Matters: This shows how using computer simulations can save time and money by letting you fix problems with your design's control systems before you build anything physical.

Critical Thinking: To what extent can virtual commissioning fully replicate the complexities and potential failure points of a real-world robotic cell, and what are the implications for design decisions based solely on simulation results?

IA-Ready Paragraph: The integration of virtual commissioning tools, as demonstrated by Raffaeli et al. (2022), offers a powerful method for verifying and optimizing the control logic of robotic cells. By simulating the interaction between virtual robot controllers and PLC environments, designers can proactively identify and resolve potential inefficiencies, leading to improved overall system productivity and reduced physical commissioning time.

Project Tips

• When planning your design project, consider how you can simulate key interactions or processes.
• Explore software that allows for the integration of different control systems if your project involves multiple components.

How to Use in IA

• Reference this study when discussing the benefits of simulation and virtual prototyping for testing control systems in your design project.
• Use it to justify the use of simulation software in your design process.

Examiner Tips

• Demonstrate an understanding of how virtual commissioning can de-risk the implementation of complex automated systems.
• Highlight the potential for performance gains through virtual optimization.

Independent Variable: Integration of virtual robot controller and PLC environment in simulation.

Dependent Variable: Overall system productivity, control logic effectiveness, performance verification.

Controlled Variables: Specific robotic cell configuration, control code used, simulation software parameters.

Strengths

• Demonstrates a practical integration of different industrial control software.
• Provides a clear methodology for virtual commissioning of complex robotic systems.

Critical Questions

• What are the key challenges in accurately modeling the physical interactions and potential delays in a virtual robotic cell?
• How can the results from virtual commissioning be reliably translated to ensure optimal performance in the physical system?

Extended Essay Application

• An Extended Essay could explore the development of a novel virtual component for a specific type of industrial robot or PLC, or investigate the impact of different simulation fidelity levels on design outcomes.
• Research could focus on quantifying the cost and time savings achieved through virtual commissioning compared to traditional methods.

Source

Engineering Method and Tool for the Complete Virtual Commissioning of Robotic Cells · Applied Sciences · 2022 · 10.3390/app12063164