Artificial Intelligence (AI)

Smarter production – with artificial intelligence

Artificial intelligence (AI) is one of the most promising technologies of our time. It is a key technology for the competitiveness of Germany and Europe. Company processes and business models can be fundamentally changed and optimized by artificial intelligence and machine learning to enable sustainable and intelligent production.

Not only can employees be supported by AI in complex analyses, but processes can also be intelligently controlled. Data-driven process modeling can improve product quality and reduce scrap rates. Due to the digitalization of manufacturing and production processes, the amount of data collected is growing. This opens up a wide range of potentials, for example, in the field of automated modeling, online condition monitoring, anomaly detection, adaptive control systems, and simulation technology, etc. Human-robot collaboration and interaction (MRC, MRI) also play an important role in industrial production. Industrial robots are becoming smarter, more flexible, and safer through AI. In addition, efficiency and flexibility in production can be increased through AI-supported process optimization, predictive maintenance, and quality assurance (keyword »Industry 4.0«).

Challenges in the use of AI

Even though some companies have already recognized the competitive importance of artificial intelligence, implementing it in their own businesses is not always easy. Small and medium-sized companies in particular often face major challenges. They often lack the appropriate data basis, qualified specialists, or sufficient trust in the new methods. Especially concerning data sovereignty or the safeguarding and certification of AI systems, skepticism often still prevails. At Fraunhofer IGCV, we see ourselves as mediators of these new technologies and would like to shape the transfer of the latest findings from research to industry together with you.

Artificial intelligence in manufacturing companies

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. To make the potentials of AI-supported production usable for our partners, we focus on the concrete applicability of AI solutions in the company. Various projects at Fraunhofer IGCV, for example, deal with the further development of products and processes.

Machine learning and AI methods enable direct benefits here: For example, the use of storage space and thus storage costs can be kept as low as possible by an AI controlling in advance which products logistics centers store and how many of them at what time. The placement of goods on shelves is optimized so that as little space as possible is required. Prices are adjusted flexibly as the expiration date of food products approaches.

Example project »REIF | Resource-Efficient, Economic and Intelligent Foodchain«:

From theory to practice: possible applications of artificial intelligence

Although the algorithms and methods of artificial intelligence have been known and available for some time, their simple transferability into industrial practice is not always given. Manufacturing companies repeatedly face similar challenges when applying artificial intelligence methods:

  • Data availability and the corresponding computing power must be available and usable.
  • Often, sufficient expertise in AI methods or machine learning is still lacking.
  • Prerequisites for the methods in one's own company are not known.
  • The potential benefit of AI solutions in one's own company is difficult to assess.

Numerous research and industry projects at Fraunhofer IGCV have shown that the following questions, in particular, must be answered when implementing AI applications in operational reality to meet the aforementioned challenges in a forward-looking manner:

  1. Where do I have potential?
    Added value: Identified AI potentials
  2. What AI applications do I want to implement?
    Added value: Application roadmap with which potentials are achieved
  3. What data do I have and what value does that data provide for AI applications?
    Added value: Creating transparency concerning the available data
  4. What data-based correlations and recommendations for action can be identified?
    Added value: Recommendations for action that improve processes
  5. What models do I need to use to get the most out of my data? How can these results be visualized?
    Added value: Rapid use of data in everyday life, new AI applications
  6. How can I train my employees and develop a data-driven business model?
    Added value: Generation of knowledge and new earnings potentials

Our services and insights from relevant AI projects

We transfer key findings from science and research precisely to your individual challenges. In this way, we support you in analyzing and exploiting the potential of AI methods in your company.

  • We help you transfer AI methods to your own production and logistics processes.
  • We support you through joint data pre-processing in the targeted selection of suitable algorithms and artificial intelligence methods.
  • Through intensive training and testing of models, we jointly test different use cases and qualify your employees.
  • Employing detailed analysis and interpretation of the models and correlations, relevant process parameters and cause-effect relationships can be identified.
  • The insights gained then make it possible to derive explanations and recommendations for adapting the processes - specifically in your company.

AI solutions at Fraunhofer IGCV



Potentials of AI to optimize the ability to plan and control value creation in the food industry: REIF (Resource-efficient, Economic and Intelligent Foodchain).


AI-based quality assurance of castings through anomaly detection.


Condition monitoring in Binder Jetting: A camera inside a 3D printer.


Semantic modeling of the complex dependencies of additive manufacturing processes.


A showcase of end-to-end digitized pultrusion.


Intelligent battery cell manufacturing with AI-supported process monitoring based on a generic system architecture.

Further competences and lead topics at Fraunhofer IGCV



We are shaping the way into the future...

...of efficient engineering...




...networked production and...


Multi-material solutions

...of intelligent multi-material solutions!

Biological Transformation

Biological transformation offers great potential for a sustainable business.


Composite Recycling

With numerous research projects along the entire recycling chain, we are ensuring a more sustainable approach to this group of materials. 

Cooperation with Fraunhofer IGCV

We will be happy to find an individual solution for you.

Range of services

This is what Fraunhofer IGCV can specifically do for you.


FAQs on collaboration with Fraunhofer

Here you will find an overview of the most important questions in the context of an initial collaboration.

contact persons

All contact persons for concrete project inquiries.