DIAMOND – Digital plant modeling with neutral data formats

Digital plant modeling with neutral data formats

In the DIAMOND project, a Common Data Model that can be adapted to different use cases and a modern data exchange via common data spaces are being developed and tested. In addition to technical solutions, the organizations and needs of involved persons of the companies are also considered. The focus of the project, which is funded by the EU and the federal government and has 25 consortium partners. It is on the process of production plant planning and design in the automotive industry.

The increasing penetration of digitalization has consequences for both the product vehicle and its production. The DIAMOND project is dedicated to the upcoming transformation and the associated changes.
Here, end-to-end, data-supported solutions are being established for the creation, transfer, and use of digital twins in the plant design process.n.
The Goal is to achieve high market penetration through neutrality and scalability.
Among other things, the digital "Common Data Model" is intended to accelerate project times in the engineering of production plants for faster integration of new vehicles and drive technologies. Process acceleration over the entire life cycle leads to sustainable operational improvements while simultaneously increasing quality.
Costs can be reduced through flexible, dynamic multiple use and investments avoided through predictive testing processes.
In addition, the focus is on further development of resilience in order to be able to compensate for disruptions in the interlinked, global value chains as efficiently as possible.
This will create the basis for a sustainable implementation structure of Industry 4.0 in the value chains of vehicle manufacturers and suppliers.
Besides, the novel data-oriented production processes will simulatively accompany both the safeguarding of operational elements and the enabling of structural change.

Data consistency

Data Structure

Sustainability

Data consistency

Data Structure

Sustainability

Data consistency

Why?

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.

How?

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.

What?

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.

Sustainability

Why?

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.

How?

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.

What?

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.

Interoperability

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.

Data efficiency

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.

Increasing efficiency

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.

Standardization

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.

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