Editor's Choice


Virtual commissioning evolves into a model-driven digital twin

August 2020 Editor's Choice

Virtual commissioning (VC) technology allows manufacturing and control engineers to simulate manufacturing production systems and validate that the physical packaging machines, conveyance systems, automotive production systems, robotic work cells, and controls (PLCs, drives, motors, sensors) will all physically function as designed and built.

Virtual commissioning uses a virtual model that represents an accurate and realistic 3D simulation of mechanical, electrical, and controls systems to validate the physical functions of a production system prior to actual physical implementation. The inherent complexity of integrating the different engineering disciplines previously necessitated a rather labour-intensive commissioning process. VC technology and applications were developed to reduce or eliminate the physical process, shortening the time to product launch, and ultimately producing significant cost savings.

The initial virtual commissioning applications emerged as part of the overall digital manufacturing portfolios offered by product lifecycle management (PLM) suppliers. Here, 3D CAD models of machines, robotic work cells, and production systems could be created and used to simulate motion and production functions. The other part of VC was to create software that would emulate the control systems (PLCs, robots, etc.) to be able to virtually test the physical system. Today, we are seeing the convergence of traditional VC with the more recent emergence of the concept and implementation of the digital twin.

The evolution of virtual commissioning

The automation industry has long acknowledged the benefits of using virtual models to simulate the performance of physical systems to enable integration issues to be identified before entering the time-consuming and expensive process of physical commissioning. To implement VC, however, the virtual factory model must be an accurate representation of the system. While these types of simulation models were used with some success in the aerospace and automotive industries, this was not the case in the overall automation market.

Control engineers and automation researchers have organised four categories of general controls development:

• Physical commissioning, which involved testing the physical systems (factory production systems) against the hardware without the assistance of virtual modelling tools.

• Model-in-the-Loop (MiL) where the application creates a logical model of the PLCs, HMIs, and electrical and mechanical systems. The application connects the logical model to a simulation model of the production system.

• Software-in-the-Loop (SiL) is the software code that runs the logical model.

• Hardware-in-the-Loop (HiL) testing, which uses a virtual production system model to test the hardware controllers. This is sometimes referred to as controls emulation.

The actual virtual commissioning process is usually an iterative approach using MiL, SiL, and HiL concurrently. Once the MiL is complete, controls engineers use SiL testing to verify that the logic in the model is consistent once it has been compiled into machine code. If no errors are found at this stage, final HiL testing is conducted by compiling the software onto the physical PLC or HMI. Today, suppliers of robust VC development and simulation platforms typically provide a full range of simulation and VC applications that meet this approach.

Virtual commissioning becomes part of the digital twin

Today, we’re seeing the convergence of established virtual commissioning technology with the more recent emergence of the concept and implementation of the digital twin across industry and business. While VC represents the simulation and modelling of machines and production systems to validate the system and the controls that automate it, the digital twin is broader in scope and involves capturing sensor data from physical machines and systems in operation and using that data to create simulations in real time. Because of its real-time characteristics, a digital twin can simulate a system while it is operational. This allows manufacturers to monitor the system, create models for adjustments, and make changes to the system.

Model-driven digital twin advances virtual commissioning

For virtual commissioning to become a practical technology across manufacturing and automation, automation generalists need to be able to create and use the virtual models for even complex simulation applications. The development of advanced, model-driven design methods has taken form in what the automation industry now refers to as a digital twin. Additionally, the continuous advancement of simulation modelling applied to today’s production systems offers a much more robust and accurate virtual representation than the earlier and simpler modelling tools for VC. Moreover, the software development standards for model rendering and connectivity have been improved significantly. Taken together, these make VC more practical for the automation industry.

Model-driven digital twins

With systems design modelling tools, the creation of a model-driven digital twin can begin concurrently to the design process. Advanced simulation modelling tools allow engineers to import CAD models of machines, automation hardware, robotics, and production line equipment to build dynamic models of the automation process. Model-driven digital twins make VC more accessible and add the power of advanced simulation technology and capability to the overall automation process.

The primary goal of the commissioning process, whether physical or virtual, is to bring a completely integrated, assembled, and validated mechanical, electrical, and controls software production system into operation. The challenge for successful VC implementation goes beyond just virtually emulating controls logic for the automation hardware. It involves integrating all the engineering disciplines of mechanical, electrical, and software logic design together in a systems design approach that normalises the constraints that each system places on the other.

For more information contact Paul Miller, ARC Advisory Group, +1 781 471 1141, pmiller@arcweb.com, www.arcweb.com




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