Digital Fingerprint.

Creating a basis for an intelligent value chain


Silvio Facciotto

Department for Aircraft Design, University of Stuttgart

Digital Fingerprint

Creating a basis for an intelligent value chain

The intelligent data collection, processing and transfer across the entire value chain - starting from the idea, going through design, production and in-service to end-of-life - for the smart component and the versatile, autonomous factory of the future.


The context of Industry 4.0 demands the implementation of a digital fingerprint for each individual component. This fingerprint serves as a holistic representation of the entire product life cycle, with product development, manufacturing, assembly, and monitoring realized through automated, self-organized, and intelligent processes.


The intention is the coherent capture and intelligent networking of data throughout the entire creation process: from the initial conception, through design and process data, to in-situ data captured by integrated sensors. The application of the digital fingerprint aims to ensure significant reductions in development times and costs as well as in manufacturing scrap.

Project Progress

The project was divided into five sub-projects:

  1. Data and Semantics: Semantic characterization of the digital fingerprint.
  2. Smart Engineering: Elaboration of various simulation approaches, starting with component optimization up to the predictive representation of potential component damages under real load scenarios.
  3. Smart Component: Integration of adequate sensors into the component to capture data from both the manufacturing process and the application phase.
  4. Smart Production: Implementation of an efficient interface for production and assembly.
  5. In Service and Evaluation: Evaluation of the digital fingerprint based on real in-service data collected.

Results in Detail

SP1 – Data and Semantics

For central data storage, the Teamcenter tool was used as a PLM system, which provides a comprehensive data model for the Digital Fingerprint of all Components (DFA). An architecture depicted in the figure supports the capture of data from both production processes and ongoing operations. Additionally, a web-based portal was designed, offering users the ability to initiate measurements remotely. The data stored in the system serve not only for quality monitoring but also flow into various simulation models.


SP2 – Smart Engineering

Simulation models were developed that represent both production processes and operational loads. These models enable direct integration of the collected data into the product development process. Using virtual methods, processes and designs are continuously optimized for subsequent product generations. Specifically, the simulation of component loads in real operation, based on data from driving tests, is an essential factor for early detection and prediction of component failure. This paves the way for predictive maintenance, which can be individually adapted to customer requirements, such as type of use, climatic conditions, and terrain.


SP3 – Smart Component

During the manufacturing phase, MEMS sensors were integrated into demonstration components. These sensors specialize in capturing accelerations and temperatures, thus enabling continuous monitoring of both the production process and the condition of the component.


SP4 – Smart Production

To maximize production efficiency, all production processes are continuously monitored. This allows potential sources of error to be identified in advance, minimizing the unnecessary consumption of resources and time. The data captured during production are recorded using sensor technologies developed in TP3. Technologies from TP1 are used for monitoring and data collection. The collected data are used in combination with simulation models from TP2 to continuously optimize and personalize CAM programs.


SP5 – In Service and Evaluation

By integrating demonstrators into vehicles, driving tests can be carried out. These serve to realistically predict the lifespan of individual components. The knowledge gained from this directly reflects in the design processes and closes the loop between the real product life cycle and its digital counterpart.

Points of Contact and Successor Projects

Future developments and synergies could manifest in projects such as CATENA-X, ARENA-X, and EcoFrame.

"ARENA2036 is a lighthouse of the University of Stuttgart in the field of knowledge and technology transfer. In cooperation with our partners from science and industry and not least start ups, we have succeeded at establishing a unique innovation platform. I am personally fascinated above all by the agility and versatility of the ARENA2036, which is expressed solely by the fact that I am always discovering new projects on the hall space."

Prof. Dr.-Ing. Peter Middendorf

Head of the Department for Aircraft Design

University of Stuttgart

"In the production of the future, data will play a decisive role and the integrated use of development, production, and operational data will become the key factors for trustworthy value creation and utilization systems. For DXC.technology, ARENA2036 is already a special environment. As a leading, independent integration service provider, we can contribute to the networking of these worlds and help shape the data standards of tomorrow. The university environment is of elementary importance for the education of our young talents."

Gero Adrian & Franziska Gross

Director Advisory R&D Industry4.0 at DXC Technology & Business Innovation and Startup Relations

DXC Technology