Strengthening production processes at SMEs through the use of AI in generative manufacturing

In times of global crises such as the current Corona pandemic, companies from all industries experience supply bottlenecks. These affect the procurement of spare parts, purchased parts, or prototypes. A breakdown in the supply chain hits small and medium-sized enterprises (SMEs) particularly hard. They usually have a smaller product portfolio than large companies and find it difficult to switch to alternative supply chains.

This research project supports SMEs in particular by digitalizing production processes to build resilience and bridge supply chain interruptions with generative manufacturing. There are two main challenges to manufacturing a successful product using 3D printing:

  • Generating manufacturing data for generative manufacturing, 
  • Adjusting the process parameters depending on the number of pieces, production duration, and production time.

To generate a design suitable for 3D printing, artificial intelligence (AI) is used to exploit the experience already gained at Trier University of Applied Sciences, Birkenfeld site, through Design of Experiment (DoE) in the field of component design for generative manufacturing. The required geometries are generated using 3D scanning or parametric design. Furthermore, exemplary optimization potentials concerning, for example, weight savings are carried out with topology optimization on the digital twin of the component.

To control printing to optimum process parameters, a 3D printer is equipped with additional sensors for recording temperature, vibrations, humidity, etc., and the data is recorded. Furthermore, remote access to the printer will be integrated to reduce the need for on-site personnel through remote control.

The necessary failure parts of the companies consist of a wide variety of materials. To demonstrate the potentials of digital product optimization and additive manufacturing, exemplary spare parts are digitized and produced with different printing processes and materials (metals, plastics, fiber-reinforced plastics). 

Duration 01.11.2020 - 31.10.2021
Supported by Ministerium für Wissenschaft, Weiterbildung und Kultur Rheinland-Pfalz
Funding amount 92500 €

Project Management

Prof. Dr.-Ing. Michael Wahl
Prof. Dr.-Ing. Michael Wahl
Professor FB Umweltplanung/-technik - FR Maschinenbau

Contact

+49 6782 17-1313

Location

Birkenfeld | Building 9916 | Room 136

Consultation

nach Vereinbarung
Prof. Dr. Henrik te Heesen
Prof. Dr. Henrik te Heesen
Professor FB Umweltplanung/-technik - FR Maschinenbau

Contact

+49 6782 17-1908

Location

Birkenfeld | Building 9925 | Room 12

Consultation

Montag, 11-12 Uhr, nach Vereinbarung per E-Mail/Monday, 11-12 h, by arrangement via mail

Contact

Trier University of Applied Sciences, Environmental Campus Birkenfeld
Institut for Operations and Technology Management (IBT)
Campusallee 9925
55768 Hoppstädten-Weiersbach
Germany

back-to-top nach oben