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To achieve data consistency in the heterogeneous tool landscape of the digital plant design process, consistent standards must be applied to data structures and data exchange technologies.
Neutral and scalable data models that can be mapped using standardized data exchange technologies enable a high level of market penetration, which ultimately leads to a significant acceleration of processes along the entire value chain in the plant design process.
A neutral and digital Common Data Model for individual machines, production resources and components, but also for products and processes, will form the basis for the digital plant creation process from initial planning to commissioning of the production plant and will be used to derive standards and interfaces in the form of demonstrators.
The complexity of plant engineering is increasing rapidly with the digitization efforts of companies. The implementation of holistic information networking must be oriented toward meeting all process requirements between production planning, operations and the supplier network. The aim is to develop a common data structure and validate its adaptation using selected scenarios as examples.
We will identify exemplary elements from jointly developed scenarios and validate them based on target images regarding their value, idealized data structures and functional interaction. In this way, we will show the way in which a digitization fabric (digital threads) is created piece by piece and serves the corresponding processes.
Real examples provide proof of applicability using appropriate functional elements and detailed documentation. Companies can thus build migration strategies to add secured modules to a company-specific digitization strategy.
A sustainable digital twin requires comprehensive planning, a clear vision, consideration of technical and organizational requirements, thorough analysis of the business process, close collaboration with users and stakeholders, maintainability and adaptability, creation of competencies and capabilities, training and support for use, and consideration as a long-term investment with resources provided.
Important tasks in creating knowledge about digital twins include understanding and communicating the benefits and application areas through informational materials, training, and workshops for various audiences, ensuring transparency in decision-making by providing information about costs and benefits, and creating a network of experts to support knowledge transfer and implementation of projects. It is important that these efforts are maintained and updated on an ongoing basis.
To improve the use of digital twins, it will be helpful to provide use cases, training materials, deployment concepts, a cost-effectiveness calculator, data checks, and other tools. These resources can help sharpen users' imaginations, simplify implementation, improve user skills, and monitor data integrity and quality. It is important that these resources are regularly reviewed and updated to ensure they meet current requirements and developments.
Thanks to its standardized structure, the Common Data Model enables a uniform exchange of data and information between different systems and software applications. This facilitates collaboration between automotive manufacturers and their suppliers, as the data is uniform and easy to understand. As a result, collaboration can be made more efficient and productive.
Through its standardized structure, the Common Data Model enables a structured exchange of data and information along the plant manufacturing process between automotive manufacturers and their suppliers, regardless of the software used. This facilitates collaboration and enables data and information to be exchanged more quickly and accurately, improving the efficiency and quality of the plant manufacturing process.
Thanks to its standardized structure, the Common Data Model enables a fast and efficient exchange of data and information along the plant manufacturing process between automotive manufacturers and their suppliers. This can help to shorten project times in the development of production plants, as the data is available in a standardized form and can be processed more quickly. This can speed up the integration of new vehicles and drive technologies, which can increase the company's adaptability and competitiveness.
Through its standardized structure, the Common Data Model enables a uniform and cross-company exchange of data and information, regardless of the software used. This can significantly improve data exchange for both new and reused production equipment, as data is available in a uniform state and can be exchanged faster and more accurately. This can increase collaboration and the efficiency of the plant manufacturing process.
Here you get insights into the current results of the research project DIAMOND
An analysis of the involved process steps and the resulting data flow
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The federal government has allocated a multi-billion amount in the economic stimulus package to address the structural changes in the automotive industry, aiming to initiate a sustainable, rapid, and technology-neutral transformation within the sector.