Events

  • ProduktionNRW
  • Experience Exchange (open to participate)
  • Digital format

Artificial intelligence in mechanical engineering - practical solutions for NRW

places available
Free event

AI and machine learning open up new opportunities for mechanical engineering - from process optimization to quality assurance. In the exchange of experiences, we will show practical examples of how companies are using them to increase efficiency and the degree of automation.

places available
Free event
Mon. 09.02.26 13:30 - 15:00 hrs.
Event language
  • German

AI and machine learning open up new opportunities for mechanical engineering - from process optimization to quality assurance. In the exchange of experiences, we will show practical examples of how companies are using them to increase efficiency and the degree of automation.

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Artificial Intelligence (AI) is increasingly becoming part of our society, and particularly the mechanical engineering sector. Despite the strong interest and promising potential, these opportunities have by no means been fully exploited.

In our online event “AI Solutions for Mechanical Engineering – NRW”, we will showcase practical application examples and product-neutral technology contributions, demonstrating how to successfully embark on AI and Machine Learning (ML) and embed them sustainably within companies.

Purpose of the Online Event

The speakers will provide practical demonstrations of the diverse applications of AI in mechanical engineering. This time, the focus will be on AI applications in production: business processes can be monitored, analysed, and automatically improved – with the aim of measurably increasing efficiency, quality, and production safety.

In addition, participants will learn practical approaches for successfully implementing machine learning solutions and integrating them into existing processes. The event will offer both technical insights and organisational aspects, enabling participants to directly identify which steps make sense for their own projects.

Programme

The presentation will give participants a hands-on insight into the use of AI in mechanical engineering. Based on industry case studies, two key topics will be addressed:
  • Energy Efficiency improvement through Machine Learning in automation – a machine-expert-centred approach showing how ML solutions can be scaled and integrated into production processes to measurably increase efficiency, productivity, and the degree of automation.
  • AI assistance systems for quality monitoring of large-scale plants – how artificial intelligence can be used to efficiently monitor production processes, detect errors at an early stage, and ensure sustainable quality.

Target Audience

The event is aimed at all those interested in the sector and seeks to reduce widespread reservations about ML. Participants will also have the opportunity to contribute their own questions to the discussion and actively engage with the topic.

Moderation: Kevin Löpke
Registration deadline: 6 February 2026

If you are unable to attend despite registering, please let us know briefly.

To ensure an efficient dialogue, the number of participants is limited. Registrations will be processed in the order in which they are received.

Participation in the event is free of charge.

Organizer

The event is offered by ProduktionNRW in cooperation with VDMA Software and Digitalisation. ProduktionNRW is the cluster for mechanical engineering and production technology in North Rhine-Westphalia and is managed by VDMA NRW. ProduktionNRW serves as a platform to connect companies, institutions, and networks with each other and along the value chain, to inform and promote them. Key parts of ProduktionNRW’s services are funded by the Ministry of Economic Affairs, Industry, Climate Action and Energy of the State of North Rhine-Westphalia.

Agenda

Mon. 09.02.26

1.  Welcome and introduction to the topic

Kevin Löpke, Consultant, ProductionNRW

2.  VDMA activities on AI and evaluation of the AI survey

Carsten Rückriegel, Consultant, VDMA Software and Digitalization

3.  Field report from VDMA member area I

Dr. Carlos Paiz Gatica, Product Owner Industrial Analytics, Weidmüller Interface GmbH & Co. KG

4.  Field report from VDMA member area II

Dr. Florian Kruse, Partner, Point 8 GmbH

5.  Exchange of experience

All

6.  Conclusion & outlook

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