As near-real-time images of real systems or processes, digital twins support the monitoring and optimisation of the real system or process with the help of innovative technologies such as IoT, machine learning and virtual or augmented reality.
The next stage of evolution
The most cost-effective and least risky way to study the impact of new technologies and to assess and rank trends is to use simulation models. These make it possible to study impacts in complex environments and to track decisions over time.
Digital twins represent the next evolutionary stage of simulation models. In contrast to classical simulation, a digital twin represents the real system or the real process over its entire life cycle. States of the real system are recorded continuously and in real time, so that the current behaviour in the real system can be analysed with the help of the digital twin.
This is done with AI methods and thus allows predictions, e.g. for optimising the real system, to be determined without risk.
Depending on the application, the knowledge gained can be automatically transferred back to the real system as actions.
The development of industry and society is characterised by a constantly growing number of influencing factors with simultaneously shortening innovation cycles. Getting to grips with the associated complexity is a daily challenge in many industries and sectors.
To manage this complexity, with the aim of securing their competitive advantage, companies have started to collect as much data as possible about their business activity and draw useful conclusions from it.
Digital twins of real business activities use this data and thus combine different methods and technologies to make the challenges manageable for companies.
Advantages and benefits of digital twins are already implied in the name: a digital copy of reality where “seeing”, “thinking” and “acting” are completely risk-free.
The concept of the digital twin offers the following opportunities:
- Insight: A digital twin increases visibility and transparency in larger, interconnected systems, such as a production factory or an airport. It can be used as a communication and documentation mechanism, e.g. to understand and explain the behaviour of individual machines or processes at different levels.
- Predictability: Using different modelling techniques (simulations, mathematical or data-based), a digital twin can be used to predict future stock levels or operational disruptions.
- Continuous improvement: The multitude of technologies used in a digital twin makes it possible to continuously improve the real process in the future through know-how and infrastructure. The possibility to simulate different scenarios, starting from the current state of the business activity, supports the derivation of suitable options for action.
- New business models: Digital twins not only promote traditional business models, but also enable new, data-driven or product-as-a-service business models to be developed.
Digital Twins offer a multitude of opportunities for your business
With our Digital Twin solutions, we are able to offer our customers cost-effective, virtual environments. These Digital Twins allow you to conduct research and make optimised decisions without putting operations or business at risk.
Digital Twins increasingly permeate our economic, public and private environments. The underlying and applied key technologies – edge computing, Internet of Things (IoT), machine learning and simulation – are increasingly used. The ENGINEERING team of experts supports you in the planning, creation and operation of your Digital Twin.
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Would you like to show your colleagues the clear added value of the Digital Twin? Please do not hesitate to contact us if you have any questions, including the individualisation of the documents according to your requirements.
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