AI meets production - intelligent technologies as a driver of industrial transformation

The event took place as part of the online series "Transformation - Digitalization and Transformation: Opportunities and Challenges for SMEs". Dr. Oliver Böhm, project manager of the AI Production Network Augsburg at Bayern Innovativ, gave a well-founded overview of the state of the art, current practical examples and the next development steps on the way to the smart factory - always keeping an eye on the challenges and opportunities for SMEs. We have compiled an overview of the key learnings from the event for you below.

1. industrial change needs data-based answers

Rising global competitive pressure, increasing complexity in production, a shortage of skilled workers and stricter sustainability requirements - the challenges for manufacturing companies are enormous. Especially in a high-wage country like Germany, production processes need to become more efficient, more flexible and more resource-friendly. AI is seen as a key enabler that can address these requirements at the same time. Around 40% of industrial companies are already using AI applications and a further 35% are planning to introduce them in the near future. Interest is growing in SMEs in particular, even if many companies are still in the early stages.

2 From predictive maintenance to generative design

The fields of application for AI in production are diverse:

• Predictive maintenance: Sensor data is evaluated in real time to detect wear patterns and avoid downtime. This can reduce unplanned downtime by up to 70%.
• Automated quality inspection: AI-supported image processing systems detect defects in components immediately - significantly reducing rejects and rework.
• Production optimization: Intelligent analysis of material flows and energy consumption allows processes to be dynamically controlled and resources to be used optimally.
• Intelligent robotics: Collaborative robots with AI control relieve the burden on skilled workers and take over monotonous or ergonomically demanding tasks.
• Assistance systems for workers: human-centered AI solutions support employees with digital instructions, quality checks and ergonomic recommendations.

Generative AI is also opening up new dimensions in product design. AI algorithms design components that require significantly less material for the same stability - an important lever for lightweight construction and sustainability.

3 Why SMEs are still hesitant

Despite growing openness, SMEs still face typical hurdles: a lack of data, a lack of AI expertise, limited resources and uncertainty when dealing with complex systems.

This is where Bayern Innovativ comes in with the AI Production Network Augsburg. The network pools expertise from science, research and industry, finds suitable partners and provides support with funding. The aim is to make it easier for SMEs to get started with data-driven production processes - from the first pilot project to scaling up.
It is important to start small. If you start with clearly defined pilot projects, you gain experience and build trust within the team. The path to AI-driven production is a learning process, but one that is worthwhile.

4 Success factors for implementation

Practical projects show: Successful AI implementation succeeds when companies first build up their data infrastructure, integrate external expertise and test standard solutions before investing in in-house developments.
Today, new models such as AI-as-a-Service enable the use of powerful AI tools without large upfront investments - ideal for smaller companies that want to see results before scaling further. In addition, human-AI collaboration is crucial. AI does not replace specialists, but expands their scope of action. Humans remain at the center - as knowledge providers, decision-makers and creative problem solvers.

5 Outlook: Networked, explainable and sustainable AI

The future of industrial AI lies in networked ecosystems. With Industrial IoT, 5G and cloud architectures, machines, sensors and systems communicate in real time - the factory of the future will be self-organizing, adaptive and resilient. At the same time, regulatory issues are moving into focus: the EU AI Act is creating clear rules for the safe and transparent use of AI systems.
Generative AI, co-pilots and learning assistance systems will fundamentally change the world of production in the coming years - provided that companies remain willing to experiment and learn.

6 Bayern Innovativ as a partner in change

With the AI Production Network Augsburg, Bayern Innovativ specifically supports the transfer of research into industrial practice. Through cooperation with universities, Fraunhofer Institutes, chambers of industry and commerce and digital centers, practical application examples, training courses and access to funding are created to make it easier for SMEs to get started.

Note: AI was used in places in the preparation of this text

Would you like to use the opportunities of AI in production? Please feel free to contact us!