The digital twin – a comprehensive virtual image of product and production

From concept to execution, we can help you develop your digital twin strategy. With in-depth knowledge of digital replication of manufacturing and products, we provide comprehensive support to enterprises aiming to harness digital twins to refine operations and achieve sustainability milestones. Our service ensures a seamless transition into digital twinning, making your business future-proof and ready for the next wave of innovation.

Our service

• Strategic roadmapping for digital twin integration, tailored to your business needs.
• Customized guidance for digital twinning of processes and products, enhancing operational efficiency and market positioning.
• Access to expert insights, propelling you towards sustainability targets and advanced data analytics.

By tapping into the transformative potential of digital twins, our services empower your decision-making, boost operational efficiency, and elevate your product value. Embark on the path to digital innovation and sustainability with us. Contact André Gilerson today to explore how a tailored roadmap to the digital twin can improve your business and unlock new dimensions of growth and environmental responsibility.

We are working on various solutions for production processes in turbomachinery manufacturing that can reduce or even completely avoid costly manufacturing errors:

The data collected from the design and development of the complex engine components serves as the basis for the virtual image. All production and sensor data is stored individually for the respective product in the digital twin, so that it carries the complete production history including project and order data.

The extended models with product, production and usage data are available for analysis and accelerate process development and optimization in individual and series production.

In the event of maintenance work, the current status of the component can also be recorded and analyzed using the data stored in the virtual model.

If you have any questions about the digital twin of engine components, please contact Philipp Ganser.

Glass forming is an established, efficient manufacturing process for the replicative production of complex-shaped glass optics. During the production process, however, thermal and material influences often lead to a non-tolerable shape deviation of the glass components.

To avoid this shape deviation, Fraunhofer IPT has developed a numerical simulation tool for glass forming. Using the simulation, geometric deviations such as glass shrinkage and optical changes such as the "index drop" can be predicted for the first time and it is possible to realistically map the design of the mold inserts and process control in advance of production. In this way, the use of the simulation tool can significantly reduce product development costs.

Comprehensive models for predicting the forming result

In order to take all relevant influencing factors of the process into account in the simulation, Fraunhofer IPT is carrying out fundamental work to develop a comprehensive process model.  This includes the implementation of a viscoelastic deformation and material model as well as a thermal model that describes the non-uniform temperature distribution within the glass and the tool. Based on extensive test series, Fraunhofer IPT has precise knowledge of the material properties of optical glasses and the corresponding tool materials.

If you have any questions about the digital twin in glass forming, please contact Cornelia Rojacher.

Digital product twins in battery cell production enable structured consolidation and management of data, information and models that are assigned to a specific instance of a physical intermediate or end product, for example an electrode roll or a battery cell. Descriptive and technical product data is merged in a global data structure and semantically linked. This allows the structure and configuration of the product to be digitally mapped and enriched and linked with data on external environmental influences and relevant process data. Examples include machine parameters from individual processes such as target values for the calender gap or sensor values that are recorded during individual production steps.

The digital product twin makes it possible to create a virtual representation of the products that evolves dynamically across the entire battery cell production process chain. In this way, all information on materials, framework conditions and production steps of the product can be tracked in detail. The findings from this not only support effective quality assurance, but also allow systematic feedback of product quality features with specific production parameters. In this way, potential improvements to products and processes can be identified and product quality can be continuously improved. The digital product twins make it possible to view the properties of all intermediate products involved as well as process data from upstream production steps in much greater detail than before. Only through this linking is it possible to influence the production environment in a context-sensitive manner.

A special feature of the digital product twin is the large number and variety of intermediate products that have to be referenced with each other. These include the electrode pastes and the electrode roll for the anode and cathode, which are combined in the digital twin of the battery.

If you have any questions about the use of a digital twin for battery production, please contact Frederik Bennemann.

The use of digital strategies to predict product quality does not stop at semi-finished products made from fiber composite materials. In order to make the machining processes of thermoplastic and thermoset materials more efficient and sustainable, it is necessary to record and evaluate production data and define optimum target parameters. The digital image can be used for this task.

For the production of pressure tanks made of fibre composites, we use the digital shadow to optimize the production process along the component and ensure component quality.

In thermoplastic tape laying, constant process conditions such as uniform temperature distribution must be present for optimum production results so that residual stresses in the component are kept to a minimum. The digital image can be used to derive optimized taping strategies for homogenizing the temperature. This ensures that the thermoplastic tapes are processed into components of the highest quality.

If you have any questions about the use of a digital twin in fiber composite technology, please contact Henning Janssen.

One area of application for the digital twin is in the representation of machines and systems in production. One example of this is the presentation of information and data in a dashboard that serves as a human interaction point. During a process, the data is recorded directly in the machine and merged in a time series database.

In addition, 3D models of the machine can be rendered or pre-rendered for use. This information and data visualizes the current status of the equipment, which can be read on the PLC HMI of the machine itself or standing in front of the machine. By using additional information about the equipment and the machine process, key figures about the machine performance and the stability of the machine process can be calculated. In this way, a range of different data from different sources can be used in targeted data processing steps to create a helpful summarized display for users in production.

This simple form and implementation of the digital twin already allows essential live conclusions to be drawn about the physical object, so that process parameters - which are still largely manual today - can be adjusted. Further use cases that build on this application scenario are already part of predictive and prescriptive analytics, such as the predictive maintenance of wearing parts or fully automated, adaptive process control.

The digital building twin maps the information that is important for the construction of a factory building: In addition to sensors and IT systems, the data basis includes plans, models, drawings, material and supplier data, environmental and sensor data as well as field and user data. The two biggest challenges here are the high number of different stakeholders in construction operations and the heterogeneity of the available data sources. Unified exchange platforms can create synergies and provide uniform access points and standards for processing information.

The digital twin can provide various services for the user: For example, construction progress can be continuously monitored during the construction phase of a project. In addition, virtual inspections offer high added value for the project partners at an early stage. The optimization of planning statuses and the automatic adjustment of factory layouts and material flows also help to better organize real construction activities.

The factory twin not only offers added value through a better exchange of information right from the planning stage, but also through virtual inspections during the construction phase. Operators also benefit during the use of the building through a variety of options for holistic optimization of the environmental parameters of their production, for example through automated conditioning of clean and dry rooms.