The Design Twin Has Arrived and Must Stay

Summary

This article refers to a design twin being used in industry for an end user that regards their production process and quantified results as proprietary intellectual property.  However, by referring to this anonymous user, we show the design effort of a process expansion and improvement project has been reduced by several months. This design twin has clearly shown tangible benefit for the user.

One of the enabling technologies for Industry 4.0 is the digital twin, the formal definition of which is being addressed within the ISA working group focused on this technology (ISA Smart Manufacturing and IIoT division - Digital Twin workgroup):

• Digital data that represents the physical process
• Intelligence is embedded in software that applies this data 

One of the conclusions reached by this workgroup is that a subdivision into types is necessary to clearly define the characteristics of the delivered product.

Among the set of digital twin types identified by the ISA workgroup is the Design Twin, which aims to assist in the design and evolution of a physical system to demonstrate its capabilities and performance.

Digital twin, what for? 

But when talking about digital twins, a large professional sector does not identify them as a key part of the development lifecycle of a product or service.

That is why in this article we talk about a real use case (take it as a set of utilities for various use cases), in which the development of the digital design twin was crucial for the success of the project. A well-known car manufacturer in the United States is considering an extension and improvement of its assembly line to increase capacity and improve the productivity and safety of the facility.

The line is a continuous skid transit system over 2 km long. When considering the refurbishment, there are several key parameters that need to be adjusted, such as the number of simultaneous skids on the line or the speed of the skids, so that there are no stoppages or blockages on the lines due to lack or excess of material. And not only that, but also questions such as where exactly to place the multiple sensors on the line related to the kinematics of the process or optimize distances between process stations with different operating times based on the input material.

The digital twin arrives to help

To be able to make the calculations, it is necessary to set the optimum values of other parameters of the installation that directly influence the process, such as the operating times of elevators, operating times of assembly machines, technical stop times, shift changes, minimum and maximum number of skids in inspection areas and others, whose combination will allow optimizing the production of the installation.

The digital twin also helps in taking decisions such as the number or location of operating stations, as well as fine-tuning of their operating times.

And the twin will continue to help

After plant start-up, the digital twin allows further adjustments to be made to the plant design. The knowledge of real production data can be fed into the twin so that it can continue to be used to adjust other sets of secondary parameters that influence sub-processes, to be applied once the best possible combinations have been found.

Maintaining the twin also allows future expansions, changes, or upgrades to be addressed with accurate baseline data, or maintenance shutdowns to be planned in a way that minimizes their impact on the plant's production.

Therefore, the twin will be a Siamese

In conclusion, the digital design twin is a real and necessary tool when facing any project nowadays, which provides great added value to all participants in the execution of a project, and with its proper maintenance, allows the property to anticipate and optimize the result of its future investments.

The benefits of investing in a design twin in the commented use case are quantifiable since the start-up was shortened by two months and production began with the adjusted values, requiring only verification that the digital twin set points were correct.

This time gained benefits both, the companies that carry out the mechanical and electrical implementation of the installation, and the end customer, it is a clear example of a win-win relationship.

And these benefits do not only appear in the initial stages of a project but continue throughout the life cycle of the facility and provide added value to all facility personnel by improving their decision making and therefore improving the overall productivity of the facility.

This article comes from the Smart Manufacturing and IIoT Division of the International Society of Automation (ISA).  It is part of the ISA Smart Manufacturing & IIoT Technical Article Series.