ProKI – AI in production

ProKI is a nationwide demonstration and transfer network for AI in production. In ProKI Darmstadt, methods of artificial intelligence for forming technology are demonstrated. Additionally, the transferability to other production processes is shown.

Coordination: Stefan Seyfried M.Sc. M.Sc.
Contact person in the research groups:
Jannik Rosemeyer M.Sc. (CiP)
Borys Ioshchikhes M.Sc. (ETA)
Leonie Meldt M.Sc. (MiP)
Fabian Gast M.Sc. (TEC)

Duration: 01.10.2022 – 31.12.2024
Funded by: Bundesministerium für Bildung und Forschung
Website: www.proki-darmstadt.de proki-netz.de

Motivation

With more than 200 different processes, forming technology forms the backbone of the German metalworking industry, both in semi-finished product and component production. However, two new trends are endangering the long-standing success of German companies in forming technology and forming machines: on the one hand, the increasing complexity of forming processes due to more demanding materials as well as higher flexibility requirements and, on the other hand, the disappearance of personal experience-based knowledge of long-standing employees due to their retirement from the companies. Against this background, artificial intelligence (AI) offers considerable potential for increasing the competitive strength of companies active in forming technology. However, the Scientific Society for Production Technology (WGP) identifies deficient utilization levels of AI technologies in the German production landscape in this context. Differences between small and medium-sized enterprises (SMEs) and large corporations are particularly striking, and these are especially evident in the area of forming technology. There are various reasons for this, resulting from the lack of AI-specialized skilled workers but also from the strong specialization of the individual processes and technologies and the resulting difficulty in obtaining sufficient amounts of data, the fear of an uncontrolled outflow of know-how, the lack of proof of the economic viability of AI use and the still insufficient transfer of research results to SME-specific industrial environments.

Objectives

In order to make the extensive potential of AI in forming technology visible and to open it up for use, especially in SMEs, and thus to strengthen their competitiveness, the ProKI-Darmstadt center is making a decisive contribution to transferring knowledge from this area of technology into industrial practice. Based on a wide range of research activities in the field of data-based and AI-supported process analysis and optimization, focusing on condition monitoring, predictive maintenance, quality management, process control, material flow control and energy efficiency and energy flexibility, the Institute for Production Engineering and Forming Machines (PtU) and the Institute for Production Management, Technology and Machine Tools (PTW) can draw on extensive expertise and research and development results on the use of AI in forming technology as well as industry-related example applications. By bringing together interdisciplinary domain knowledge in the field of forming technology, information technologies (IT), data analytics, but also didactic competence transfer and work science, the center's services and offerings can be prepared in a practice-oriented manner and transferred to companies so that human-centered AI technologies can be introduced promptly in the real production environment.

Approaches

On the basis of the existing knowledge as well as experience in competence transfer, the use of AI in forming technology is to be made possible for companies. Through the services of the ProKI-Darmstadt Center, competencies and procedures are imparted on the one hand through sensitization and qualification measures in order to independently implement AI technologies. On the other hand, practical support for forming companies in the commissioning, design and technical introduction of AI is provided through implementation and stabilization measures as well as the provision of hardware (e.g. sensor systems, instructions for the selection and integration of sensor technology) and software components (e.g. data analysis tool, pre-trained machine and deep learning models, algorithms for data evaluation, etc.). This means in detail:

  • Inform: Need-based information of the target group SMEs about new AI technologies and new AI-based applications as a basis for a holistic transformation and support in tapping them.
  • Qualify: Strengthening technological and human-centered / work-shaping competencies. The AI-based transformation process is to be pushed through qualification formats, self-learning offers and offers for moderated exchange of experiences.
  • Implement: Support in the implementation of AI applications and AI technologies (e.g. through practical projects and processing of the knowledge generated there).

Acknowledgement

This project is funded by the German Federal Ministry of Education and Research (BMBF) in the funding program “ Zukunft der Wertschöpfung − Forschung zu Produktion, Dienstleistung und Arbeit ”. We thank for the opportunity to work on this project.

Funding source

Consortium partners

Project sponsor