DAiProM | Data analytics in production management

Efficiency and sustainability through artificial intelligence

Artificial intelligence (AI) and machine learning can fundamentally change corporate processes and business models. Machines produce more efficiently and sustainably, processes are intelligently controlled, and employees are supported in complex analyses. The potential applications of AI in manufacturing companies range from process and logistics data analysis, quality assurance, and machine control to completely new digital, data-based business models.

Artificial intelligence includes machine learning technologies that can be used to identify correlations in complex production and logistics processes. Algorithms and methods are used to generate complex models from a company's data representing the available knowledge. Using the latest analysis and interpretation methods, significant correlations can then be identified and evaluated.

The algorithms and methods of artificial intelligence and machine learning are now used in research and the everyday operations of manufacturing companies. Innovative companies are already using them every day to further develop their products and processes. AI applications suggest similar products, analyze and evaluate processes, and forecast demand. AI controls in advance which products logistics centers stock and how many. The placement of goods on shelves is optimized so that as little space as possible is needed and storage costs are as low as possible.

Recognizing and using new AI potential

Even though some artificial intelligence methods and algorithms have been available for years, they are only becoming usable in industrial practice due to the increased availability of data and computing power. In the operational reality of manufacturing companies, however, there are still some obstacles to the application of AI and machine learning. Often, sufficient expertise is still lacking, prerequisites are unknown, and the potential benefits are difficult to assess.

In order to identify and exploit the potential of AI and machine learning in one's own company, it is helpful to analyze key findings from science and research and transfer them to one's own production and logistics processes. Through suitable data pre-processing, the targeted selection of algorithms, and intensive training and testing of models, the scientific findings can be transferred to the company's own use cases. Using detailed analysis and interpretation of the models and correlations, relevant process parameters and cause-effect relationships can be identified. The knowledge gained then makes it possible to derive explanations and recommendations for action to adapt the processes.

Data Analytics and AI at Fraunhofer IGCV

How can the new AI potentials be made accessible for the own company? The key to the success of Artificial Intelligence in the production lies above all in the combination of application knowledge from production management and production technology as well as Artificial Intelligence and machine learning.

At the Fraunhofer IGCV, these key skills are combined, allowing individual solutions to be developed for a wide range of applications. With its key skills in the areas of engineering, production, and multi-material solutions, the Fraunhofer IGCV combines extensive application knowledge with the latest scientific findings.

What do I get from AI?

Find out together with us what action is needed and which AI applications offer the highest potential for your company.


AI level check

We can help you determine the current AI level of your company and identify the applications and products that are most suitable for you.

  • Latest findings from application-oriented science and technology
  • Proven analytical procedure
  • Analysis of production and products


Data value stream

Our data value stream analysis enables the application of state-of-the-art methods of artificial intelligence and machine learning in an industrial context.

  • Better process understanding
  • Identification of cause-effect relationships
  • Concrete recommendations for action
  • Sustainable optimization of value-added processes

Cooperation with Fraunhofer IGCV

Contact us for an individual solution that suits your business needs.

Industry solutions

The key sectors of Fraunhofer IGCV:

  • Mechanical and plant engineering
  • Aerospace
  • Automotive and commercial vehicles


We are shaping the way into the future of efficient engineering, networked production and intelligent multi-material solutions.