Shipbuilding meets digitalization: two years in the SEUS research project

Two intense years in the European research project SEUS are now behind me. Our shared goal: to drive the digitalization of European shipbuilding forward. The need for this remains as pressing as ever. The EU continuously funds research and development projects in the maritime sector to strengthen Europe’s position in global competition – which is vital for survival given the low-wage countries and extensive subsidies in markets outside of Europe.

Although European quality is highly valued in the maritime industry, cost pressures are forcing even this traditional sector to achieve massive efficiency gains and optimize its processes. This is exactly where we at CONTACT came in: as an integral partner in this research and a driving force behind the transformation, our goal was to provide the crucial data backbone required for successful digitalization.

A floating city – and what it has to do with PLM

First, we had to dive deep into the complex requirements and processes of shipbuilding to truly understand them. Through intensive discussions with shipyards, in-depth analyses, and a thorough review of the current state of research, we were able to build a comprehensive foundation of knowledge.

What really impressed us was the meticulous care with which the shipyards in this project process enormous volumes of information, collaborate securely across disciplines, and confidently navigate strict classification requirements. This involves tens of thousands of pages of test reports, calculations, manuals, and technical specifications.

What is being built here is nothing less than a small, self-sustaining city floating across the oceans – a construction process that never fails to fascinate. This is just as true for classic cargo and container vessels as it is for highly specialized cable-laying vessels, complex research ships, or military vessels.

The data backbone: connecting the maritime world

The greatest challenge lies in efficiently managing and transparently controlling the diverse information generated across all disciplines, engineering phases, and construction stages. To address this, we developed a data model specifically tailored to shipbuilding that connects all types of information, including project schedules, CAD models, simulation results, engineering designs, and supplier contracts.

Viewing the ship as a “physically massive and complex system” is crucial here. This means that instead of a few individuals keeping track of the entire vessel, a large number of engineers divide the work into smaller areas of responsibility. Depending on the engineering task and phase, they look at the ship from different angles. For example, while designing the propulsion unit focuses primarily on the architecture of that specific system, designing the ship’s hull centers on spatial layout.

A traditional product structure, which hierarchically organizes parts and assemblies based on how they fit together, cannot meet these demands. There is not one “true” product structure; instead, there are multiple viewpoints: systemic, spatial, production-centric, and module-oriented.
Many shipyards and engineering offices use a centralized system structure, as a large portion of the work involves designing, engineering, and integrating systems of all kinds. In Europe, the “SFI Group System” has established itself as the de facto standard for this purpose. This three-level standard catalog contains 4,080 entries for systems and subsystems that can be found in any type of vessel.

Schematic Diagram of Shipbuilding
CONTACT’s data model expands the standard catalog with additional perspectives.

Our IT architects designed a data model that systematically maps these other perspectives around this standard (for details, see our paper on Zenodo). In early-stage ship design, systems are first roughly dimensioned using placeholders. For example, you might specify that an engine is needed, but not yet which particular model. These placeholders – referred to below as “items” – are organized according to the SFI Group System catalogs.

As development progresses, we link these items to additional structures that form the basis of the other perspectives. Using the previous propulsion example, this could mean selecting a specific engine for that item. In addition to relevant documents, requirements, specifications, and project tasks, a CAD model can also be linked. Our partner Cadmatic enables this through a deep integration of CAD tools.

Although the project is not yet complete, a shipbuilding-specific PLM backbone, the flexible and modular CONTACT Elements platform, and the deep integration with marine CAD software already form a solid foundation for further application-level development. The sheer scale of these projects highlights why this is so critical: if even ten documents, such as specifications, CAD files, analyses, manuals, and test reports, are associated with each of the up to 4,000 possible subsystems, you quickly end up with massive amounts of data that would be uncontrollable without structured management.

On top of that, each of these documents goes through its own lifecycles, reviews, and approvals that must be coordinated both internally and with external partners. Seamless, traceable document management across corporate boundaries is therefore absolutely vital, and thanks to an extension in CONTACT Elements for shipbuilding, it is fully achievable.

To learn more about the background and the partners involved, check out the SEUS Annual Report 2025.

Design decisions in minutes – how AI supports product development

Artificial intelligence (AI) is a hot topic and increasingly important in product development. But how can this technology be effectively integrated into development projects? Together with our client Audi, we put it to the test and examined the potential and challenges of a machine learning (ML) application – a subset of AI – in a real project. For this purpose, we chose a crash management system (CMS). It is both simple enough to achieve a meaningful result and complicated enough to adequately test the general applicability of the ML method.

Expertise as the Key

ML can only be effectively utilized to the extent the underlying data foundation allows. Therefore, the expertise of the professionals involved plays a critical role. For example, design engineers enter their knowledge of manufacturing and spatial constraints, usable materials, and dependencies into the CAD model. Calculating engineers share their expertise on the simulation process, while data scientists assist with sampling and evaluation.

The creation of thousands of design and corresponding simulation models, as required for the use of Machine Learning (ML), presents a tremendous challenge without automation. The FCM CAT.CAE-Bridge, a specially developed plug-in for CATIA, enables seamless automation across all process steps. Additionally, it embeds all simulation-relevant information (material, properties, solver, and more) directly into the CAD model. The fully automatic translation into a simulation file is done via tools such as ANSA or Hypermesh.

Automated process: Sampling, DoE, model creation, simulation, evaluation with subsequent training of the ML models. (© CONTACT Software]

Precise Linking of Parameters and Results

Our approach ensures that the relationship between the CAD model and the simulation model is fully preserved. The automated calculation and evaluation of the models based on specific results create an excellent data foundation for the ML process. The vectors of input parameters with corresponding result values form the basis for the ML approach—clear and comprehensive.

Input parameters (blue) identified based on constrained result vectors (red) that meet the requirements. (© CONTACT Software)

With the trained models and their known accuracy, parameter variations can be quickly tested, and the impact on behavior can be derived—literally within minutes. Once the optimal parameters are identified, they are automatically transferred to the CAD model and the design process can continue.

Conclusion

Our project demonstrated that ML is a valid method for design engineering. The combination of parametric CAD models, simulation, and machine learning provides an efficient approach to making design decisions quickly and accurately. The prerequisite for this is a robust database and the collaboration of the relevant experts on the model. The successful results from the Audi project demonstrate the potential of our data-based approach for product development.

Why connecting Cloud PLM and CAD is important

How the integration of Cloud PLM and CAD supports efficient product development

Engineers, designers, and CAD users often experience data chaos in their daily work: MCAD files (Mechanical Computer-Aided Design) can either be archived in a technical document management system or stored in the file system. While some ECAD systems (Electronic Computer-Aided Design) offer dedicated database solutions, there is still limited communication and interaction between the MCAD and ECAD worlds. The consequence? Mutual dependencies are not consistently represented in a single software. Although workflow management systems can provide good orientation about the current project phase, they are limited to merely providing links to documents without managing them reliably. This leads to data silos that complicate collaboration among design teams and slow down the entire product development process.

The integration of Cloud PLM and CAD solves this problem. PLM software connects CAD models with all other product-descriptive documents and data, breaking down silos and organizing the data chaos.

Find out how the integration of Cloud PLM and CAD leads to more efficient product development in this interview with Kai Ruhsert and Heiko Jesgarsz, Product Managers at CONTACT Software.

What is the advantage of PLM in the cloud?

KR: Product Lifecycle Management (PLM) allows companies to manage the entire lifecycle of a product, from the initial idea and development to production, distribution, and maintenance. Instead of installing PLM software locally, cloud-based PLM provides access via the internet. This not only leads to better scalability and increased security but also lower IT infrastructure costs. The integration of employees at any additional locations is simplified, making collaboration in global product development projects more efficient.

What benefits arise from the integration of Cloud PLM and CAD?

HJ: Many design teams need to collect, review, and assess product-related documents from various sources. Providing information to ERP systems or business partners further increases manual efforts. This is not only a challenging but also time-consuming task with significant potential for errors. In some cases, media discontinuities may occur, for example, when outdated information is recorded in Excel spreadsheets and passed on to downstream processes. The results are “data silos” which complicate information exchange and collaboration, causing unnecessary efforts.

Such shortcomings are particularly problematic when it comes to fulfilling documentation and process compliance due to high customer requirements or legal changes. Or when component manufacturers want to become system providers and the new customers demand an audit-proof documentation of the entire product development process. Without a PLM system, the necessary technical infrastructure for this is lacking.

The solution to this problem: managing all relevant data of the development process using PLM software, thereby creating a “single source of truth”. The PLM system not only links MCAD and ECAD models but also establishes a consistent cross-disciplinary database. This leads to high data consistency and transparency regarding the functional and structural relationships between electronics and mechanics.

The integration of Cloud PLM and CAD is particularly valuable for many companies as it simplifies collaboration and information exchange between design teams and other departments. This ultimately makes product development and manufacturing more efficient.

What solution does CONTACT Software offer to connect Cloud PLM and CAD data?

KR: The CONTACT Workspaces Desktop. This file explorer is a powerful tool for product data management. As a central platform, the Workspaces Desktop allows designers and CAD developers to customize their work environment, organize files, promote teamwork, and access essential tools for their work. It acts as the technical bridge between CAD systems and CONTACT Elements. Information seamlessly flows between these systems and product-relevant properties are securely stored in the CONTACT Elements platform.


The structures of documents in MCAD systems such as SOLIDWORKS, NX, Catia, and Creo are complex and require intelligent team data management. CONTACT’s Workspaces Desktop meets these requirements. It relieves designers from tedious routine tasks while ensuring a process-safe database. This is achieved through standard interfaces to leading MCAD and ECAD systems, along with the most powerful multi-CAD data management on the market. Additionally, the open architecture ensures seamless business processes with other IT systems like SAP.

In conjunction with CONTACT’s Cloud PLM system, CIM Database Cloud, the Workspaces Desktop allows to access all CAD data from anywhere at any time and to link it with all data along the entire product lifecycle.

Conclusion

The seamless integration of PLM and CAD is essential to avoid data silos. Cloud-based PLM software connects MCAD and ECAD models with all other product-relevant documents and data. This ensures access to identical data at any time and from anywhere. Using Cloud PLM with interfaces to CAD systems creates a fundamental prerequisite for efficient, cross-location collaboration between design teams.

The Cloud PLM system CIM Database Cloud integrates seamlessly with leading MCAD/ECAD systems. The CONTACT file explorer Workspaces Desktop allows users to connect all CAD documents with product lifecycle data and access them from anywhere.