In the context of digital transformation, the buzzword “digital twin” comes up time and again. The concept behind it is constantly influenced by other key digital technologies. This article discusses the three most common interpretations of a digital twin, as well as the groundbreaking ISO 23247 standard for digital twins in manufacturing.
View 1: The Visualizing Twin
Existing industrial automation solutions are to be supported by a digital twin—that is the concept, which has garnered significant attention. The focus here is on a (manipulable) 3D model of the system to be automated. The vision was to use virtual or augmented reality to create a more intuitive experience for using existing automation frameworks. In short: support for the integration and organization of automation systems.
Recently, however, the concept of a digital twin has been evolving from a primarily visual representation toward detailed simulations of manufacturing facilities—in some cases, entirely without visualization, based solely on key metrics.
View 2: The Simulating Twin
Driven by increasingly complex and fine-grained manufacturing processes—and the resulting difficulty in tracking these processes—pure automation approaches are increasingly reaching their limits. This is precisely why the “new” simulation-based digital twin holds enormous potential for use in intralogistics—especially in synergy with a control system such as Flexus AG’sFlexGuide4 transport and forklift control system. Control system settings can be tested and optimized without posing any risk to the actual production system. Likewise, the time-consuming creation of realistic test cases is reduced to a minimum—as far as possible. Of course, process optimizations can be carried out independently of a control system, as long as sufficient data is collected and made available in a suitable simulation.
The main drawback of a simulation-based digital twin is that the twin’s operational capability is determined by the model’s level of customization and level of detail.
The TwInTraSys Research Project
This is precisely the problem addressed by the TwInTraSys research project. Together with OTH Regensburg, HAWL Landshut, Simplan AG, Hipp, and Mann+Hummel, Flexus AG is researching the prototypical implementation of a generic digital twin as described above.
View 3: The Representative Twin
In recent times, the guiding principles of Industry 4.0—“connected machines” or the “Internet of Things” (IoT for short)—have increasingly been incorporated into discussions about the digital twin. In this context, the digital twin corresponds to an administrative instance of a production machine, which is often referred to as a virtual agent. Unlike before, the intent is not for this entity to simulate or illustrate the production machine, but rather to control its behavior. The planning and decision-making processes of such agents overlap with artificial intelligence, thereby injecting new momentum into the topic of the digital twin.
What sets this apart from the “standard” concept of the IoT is that machines not only interact with one another through extensive networking, but actually collaborate.
One example is the FlowPro research project, in which Flexus is also participating. In short, the project team is developing an AI-powered agent system that optimizes intralogistics transport using a fleet of autonomous guided vehicles (AGVs) —the agents. For a more detailed explanation of the project’s scope, see the article “FlowPro – Automated Transportation for Tomorrow’s SAP Logistics.”
ISO Standard 23247: Automation Systems and Integration – Digital Twin Framework
The ISO standard defines the system architecture—that is, the technical structure of a digital twin. Accordingly, the standard is agnostic with regard to the actual functions that the digital twin performs in a given application. The listed functions include, for example, “real-time control,” “virtual testing,” and “synchronous monitoring”; thus, all of the described concepts are covered by the standard.
However, the standard calls for the digital twin to be closely linked to the real-world system. This is to take the form of a feedback loop that regularly transmits current load data to the digital twin, ensuring that it remains up to date. Given this requirement for synchrony and close integration, it is reasonable to expect that, in the future, a digital twin will increasingly move away from being a mere visualization and instead become a synchronously running simulation that offers additional capabilities for process control or supports such control.
In conclusion
Simply because of the diverse forms a digital twin takes and the constant evolution of our understanding of it, we will see this digital “family member” being used in operational settings more and more often. Each of the approaches described has its own rationale and areas of application. However, the trend in the future will likely move toward synchronous simulations—that is, a blend of the last two approaches—since only these can accurately model complex systems while justifying the effort involved in development and integration. At the same time, these simulations can still serve as the basis for visualization or analysis.
As evidenced by its participation in the aforementioned research projects, Flexus AG is not letting these innovations pass it by unnoticed. Anyone interested in this topic should therefore keep an eye on this blog.