Gartner, the world's most authoritative IT research and consulting firm, listed Digital Twin as one of the top ten strategic technology development trends in 2016 and 2017, making Digital Twin a very popular term in the wave of IIoT and smart manufacturing in recent years. However, this phenomenon has always made people think that it is just a term in the "concept" stage.
The earliest definition of "Digital Twin" was proposed by Professor Michael Grieves of the University of Michigan in 2003 as "a virtual digital representation equivalent to a physical product". He also suggested comparing digital twins with engineering design to better understand the production and design of products and form a close closed loop between design and execution [2].
In 2017, the well-known consulting firm Deloitte also published "Industry 4.0 and Digital Twins," which clearly described the architecture of Digital Twin. Deloitte believes that through digital twins, enterprises can achieve rapid product launch, improve operations, innovate business models, and reduce production defects. Figure 3 shows its implementation architecture.
This article is not an academic paper. We need to put "Digital Twin" into practice. In short, Digital Twin can be understood as modeling and simulating a physical production line in a virtual world, then "downloading" it to the physical world. Then, it can obtain the production status of the production line in real time, statistically present the data, transmit it to MES/ERP, etc., and accept parameters from the production line for process changes.
With Digital Twin, designers can focus on the following aspects.
What is the most difficult aspect of production line design?
Those who design production lines should know best that the most difficult and time-consuming part of production line design for manufacturing is the verification stage. This is because the production of a product consists of multiple processes, and the speed, acceleration, spacing, and other parameters of the conveyor system in each process must be verified under load to determine their feasibility. Traditionally, this process can only be carried out after the actual physical equipment has been assembled.
Clearly, virtual debugging is the best application of Digital Twin. For engineers, they can start developing programs, logic, and motion relationships before the physical production line is fully assembled or even before procurement. Then, they can perform virtual parameter calibration in the system. Once the system is assembled, they can directly download the program to achieve rapid power-on debugging. At this point, the system's parameter optimization and matching have already been completed in the early virtual debugging stage.
The second scenario involves replacing an existing production line. However, I need to verify whether the system is feasible under the new production conditions, such as adding or removing sliders.
Especially for flexible conveyor systems like SuperTrak and ACOPOStrak, their underlying mechanisms include built-in pallet anti-collision mechanisms. This prevents collisions between pallets (or the products they carry) even if a program error occurs. This mechanism is crucial for production line safety. However, in a normal production process, the triggering of the anti-collision mechanism should be avoided as much as possible to prevent unnecessary repeated acceleration and deceleration of pallets, which increases the burden on system heat dissipation and power, and may even reduce production cycle time. Digital Twin can perfectly accomplish this task. It can not only simulate the program content but also perfectly replicate the conveyor system's anti-collision mechanism. This allows us to implement anti-collision avoidance in simulation before changing equipment.
For business owners investing in costly production lines, validating their feasibility is crucial. Therefore, technologies like SuperTrak and ACOPOStrak, which leverage Digital Twin for pre-validation and planning, are essential for production line design.
(1) Know the achievable level and the optimal electromechanical matching required for it;
(2) Software development and testing are carried out simultaneously before mechanical installation is completed;
(3) Process changes can also be planned in advance;
Figure 4 illustrates a digital twin implementation architecture similar to that provided by Deloitte. The entire production line's digital twin architecture is constructed through real-time communication in the industrial field, POWERLINK, the integrated development platform Automation Studio, physical objects SuperTrak/ACOPOStrak and ABB robots, modeling and simulation software, and interconnection implemented by OPC UA.
Based on the open digital connectivity capabilities of B&R Automation Studio, the digital twin electromechanical design architecture composed of ACOPOStrak/SuperTrak is shown in Figure 5:
1. The electromechanical CAD design software provides the physical dimensions and specifications of the production line, including the geometric dimensions of the physical conveyor section and the corresponding parameters of the slider (dimensions, weight, center coordinates, etc.).
2. Control in Automation Studio: The physical movement of a slider is composed of x, y, z and rotations Φx, Φy, Φz. The mechanical parameters are combined with these control models to form a fusion of the entire physical control object.
In Automation Studio, SuperTrak/ACOPOStrak and the robot are integrated within the same software architecture and downloaded to a physical controller (an industrial PC) to control actuators such as servo drives (for controlling the robot and peripherals), as well as Trak sliders.
3. Scene Viewer interacts with CAD to create a geometric display of the production line, while Automation Studio returns the actual physical object parameters to Scene Viewer to create a dynamic graphical display.
4. When the mechanical parameters of the production line change, the CAD system provides new parameters to Automation Studio, which will then execute a new program to adjust the slider movement of SuperTrak/ACOPOStrak.
Digital twin design based on SuperTrak/ACOPOStrak can provide a completely new approach to production lines, ensuring investment security and improving return on investment.
[1]https://blogs.gartner.com/smarterwithgartner/files/2016/10/TopTenStrTechTrends2017_Infographic_Final.png
[2]Michael Grieves,Digital Twin: Manufacturing Excellence through Virtual FactoryReplication,LLC,2014
[3]https://www2.deloitte.com/content/dam/Deloitte/cn/Documents/cip/deloitte-cn-cip-industry-4-0-digital-twin-technology-en-171215.pdf
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