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Digitalized collaboration for competitive and sustainable product realization (GIMLE)

Industry 4.0

With support from:


Knowledge is a combination of experience and its analysis. The experience can be provided by different types of data, for example, human experience and feedback, machining feedback data, quality feedback data, etc. Each company has a number of sub-ecosystems, including internal and external. One of the main challenges of collaborative work is to achieve effective communication and feedback between various groups within one company, as well as between different companies. Another challenge is to manage the different data structures and incompatibility between systems.

The availability of digitized data, knowledge and models enables a paradigm shift towards new business models based on shared information and model-based collaboration. Instead of building on traditional ways of working, the vision is to create digitalized methods based on cross-disciplinary collaboration and availability of common sources of information. This includes efficient use and combinations of digital models in digital threads, and the creation of new knowledge, based on human experience and the application of AI to large amounts of data.

This project addresses this vision in the domain of industrialization within the vehicle industry. Industrialization involves analyzing production aspects such as machinability, assembly or flow of material, and modifying the product and production system for better production. Model-based industrialization means using digital models and simulations to support this process with higher efficiency.


This prestudy has the goal of making a basis for developing a reference model for model-based industrialization. Based on the status, needs and experience within the partner companies, identified white spots and state-of-the-art, the prestudy will provide a basis for planning a full project with an expanded network of partners. The long-term goal is a generic reference model for industrialization that supports efficient use and combinations of information and the design of information architectures in various companies with different conditions.


The ultimate goal of a full-scale project is to contribute to research and development of generic principles: A reference model that provides insight into digitalized collaboration – generic and reusable for different value networks.

  • Business reference model – for example: stakeholders in value network; key issues, values and risks; workflows and decisions.
  • Technology reference model – for example: ICT reference architecture; related applications and services; functionality and interfaces of applications.
  • Information reference model – for example: semantics and ontology; knowledge modelling; types of data, models, and experience used; methods for creating information from measured data (AI); information flow and principles for combining models.
  • Principles for interrelating the business- technology- and information reference models.

Project partners

- PMH Application Lab
- KTH - Department of Production Engineering (IIP)
- Scania
- Sandvik Coromant