When it comes to forward-looking corporate concepts, there seems to be no way around the digital twin. Thanks to him, companies become more flexible, thanks to him, responsible mistakes are avoided, thanks to him, product development is revolutionized, thanks to him, production runs more efficiently. Or in short, the digital twin seems to be the armament for digitization.
But how does a company get a digital twin? What needs to be considered when implementing? Are there digital twins that work out of the box? What effects does the digital twin have on the IT landscape? Andreas Dangl, expert for AI and cloud computing at Fabasoft AG, helped us answer these and other questions about the digital twin.
The term “digital twin” is usually used to digitally represent an object from the “Internet of Things”. This means that every industrial product can be dynamically digitally mapped. The DTO approach, however, as presented by Gartner in 2018, goes beyond this. By mapping the entire company organization through the “Digital Twin of an Organization” (DTO), the optimal and comprehensive planning of all processes in the company is possible. The software solutions available today and available from the cloud provide important building blocks for realizing this vision.
For the benefit in numbers: Digital Twins ensure up to 30 percent shorter throughput times and, for example, improve the efficiency of machine use in Industry 4.0 by running real-time data analysis from production by around 20 percent.
If we look at the Digital Twin of Organization, then all areas of the company can benefit from it, since it reflects the entire organizational structure and its systems, as well as the processes and workflows. Once imported into the cloud and put into operation, all processes and sequencers can be viewed from a bird’s eye view and controlled according to the defined process rules. Particular advantages are the improved integration of product development, marketing and sales.
The introduction of digital twins makes every company more strategically and operationally flexible. With digital twins you can carry out risk analyzes, carry out tests, simulations and evaluations in product development and thus explore new business models. It is even possible to enrich mirrored processes with artificial intelligence in order to constantly improve them based on real-time interactions and the resulting learning effects.
With outsourced IT, the first step towards implementing digital twins has almost been taken. Cloud providers who provide IT resources for their customers are almost always in innovation mode to protect the security of third-party data both in the storage location and during network-based access by the users.
The days when companies had to procure all of their IT capacities themselves and develop the necessary complex skills are over with the triumphant advance of cloud business. Professional IT service providers have the appropriate solution competence, especially in the far-reaching project business. One of their core competencies is to be on an equal footing with technology and market trends. DT (O) beginners are recommended to place the development of such a future solution in the tried and tested hands of these professional service providers. With them, the requirement profiles can be worked out precisely in close cooperation and then put into practice.
There is no one-size-fits-all recommendation here because, given the different companies and markets, there can be no “one size fits all” approach to IT. Information technology must always be aligned with the corporate strategy and business goals and support the necessary processes in the company itself and in the expanded environment as well as possible. Or to put it another way: In trade and marketing-heavy industries, it can make sense to address the control of many interwoven standard processes with a consistent DTO concept.
In highly complex industrial production processes with extended security requirements for the OT applications, it can make sense to first map the core processes on the shop floor with a digital twin and to filter information for efficiency increases from the real-time data flows.
As already indicated: a solution should be individually designed, designed and implemented. Decisive are the pursued market strategy, the processes and workflows already set up, the possible reusability of legacy devices and systems, but also the innovation goals and perspectives that must be included in the search for solutions. And, of course, plant security and data protection are also very important. With the exact mapping of the company organization or a production process, the necessary performance requirements are also revealed. It is important that technology is never an end in itself, but that it is tailored to existing business processes and communication requirements.
For all companies that are pioneers in the use of cyber-physical systems, there will be a huge boost in the direction of the application of comprehensive DT technologies. And these sectors are now emerging quite clearly: industrial manufacturing, automotive, retail, health care or smart cities.
The well-known large providers from the Product Lifecycle Management Software and Cloud Computing segments have already established themselves in the digital twin market. These include Siemens, PTC, Dassault or IBM, Microsoft and SAP. However, the individual manufacturers pursue strategies with different focuses, such as IoT platforms, big data, augmented reality, manufacturing execution system, advanced analytics, connected services and sensors and of course interfaces.
Yes. The services usually have standard features that are then fine-tuned to the special requirements of the user.
This is not a decision that only affects the use of digital twins, but a fundamental determination of how a company wants to organize its IT today. Since cloud computing has been able to dispel business reservations about possible security risks and has built up trust in this IT provision model with certifications and protection concepts, many companies have decided to do so. Wherever particularly sensitive data is involved, there are often hybrid models from on-premises data storage and storage and processing of data in the cloud.
Since digital twin use assumes that sensors on sensitive physical objects collect sensitive data that are continuously incorporated into the digital “doppelganger” and analyzed there for interventions, today’s cloud environments, including comprehensive security policies, are the location that are preferred for the operatio
n of this technology.
As the youngest building block of intelligent digitization, digital twins can convince with four main characteristics:
Ongoing data collection via IoT devices – for example sensors
highest connectivity for bi-directional data communication,
defined data structures for best interoperability and
appropriate user interfaces for visualization.
The connection of dashboards and control consoles for industrial production or manufacturing plants is now one of the standard features of digital twin technology.
The digital twin is the “missing link” that makes other future technologies such as IoT or augmented and virtual reality fly. And if you take it exactly, the digital twin as a representation of a physical object is itself a virtual reality. This mutual complementation of real objects / processes with virtual mirror images, or the bridging between the physical and cyber world opens up completely new possibilities of product design or disruptive business processes.
The properties of the comprehensive connectivity and defined data structures set practically no limits to the scope for interaction of this mirroring technology. It is only a question of configuration which rails are activated for the data exchange processes. System changes in the digital twin concept are always immediately synchronized with all modules involved. In this way, parameters changed from the digital twin, for example after an analysis, can be fed back directly into the program control of a production machine.
If the four basic characteristics mentioned do not mesh, the limits of the digital twin concept are reached. One of the central points for the success of digital twin projects is also the usability of the system usage by the user. It is therefore advisable to always plan, design, set up and operate digital twin applications together in a team of technology and process experts. Software system houses and cloud providers can provide external support.
Security is the meta-topic in the information economy. With regard to corporate IT, however, most cloud providers with their certified infrastructures and data centers have developed into highly reliable data trustees in recent years. The cloud model is therefore also predestined to push the use of digital twin technology.
However, since digital twins are particularly popular in manufacturing, it should be noted that the safety requirements for operating technology for controlling industrial production plants usually have to meet different requirements: protection of human life versus less downtime, just as an example. This requires maximum stability and robustness in the operation of the systems, coupled with autonomous protective mechanisms for the immediate stop of machines. Of course, these requirements must then also be guaranteed when digitally mirroring the physical production units. A further risk area is the financial or innovation areas of companies, because here attacks can cause great damage. For this reason, it is advisable to divide the business areas into zones in a DTO – i.e. a digital representation of the entire company structure – which are again protected separately, without, however, excessively hindering the cross-company data flows in the processes set up.
Ultimately, the implementation of a digital twin concept for companies is a balancing act between security and efficiency.