Möglichkeiten zur Nutzung von Additiver Fertigung im Anlauf eAM GEN6

  • Vanessa Petra Kempf

Student thesis: Master's Thesis

Abstract

Additive manufacturing is being used more and more in the automotive industry, which also concerns the BMW Group Factory in Steyr. Above all, became processes such as Selective Laser Sintering (SLS) and Fused Deposition Modeling (FDM) are used. Furthermore, processes such as Stereolithography (SLA) and Selective Laser Melting (SLM) are also increasingly coming into focus.
The strengths and weaknesses should be included when applying and selecting the processes and the associated material. In addition, the application environment for using additive manufactured components must be considered before printing.
This work provides an insight into the additive manufacturing processes which is used at BWM Group Factory in Steyr. Bases on a current analysis, filed of application were documented and identified. On the foundation of the quality data, further fields of application were to be identified during this elaboration.
The evaluation of this quality data is very complex and time-consuming. The data must be extracted form many software programs and the following process must be ordered manually to generate correlations during the evaluation. In addition, the data recording is not standardized, which leads to further problems in generating correlations.
This is the point where the newly generated chatbot should provide a remedy. With the help of increased data transparency, which increases the responsiveness of the company, the advantages of AI-supported (real-time) evaluation and the fast, flexible and tool-free use of additive manufacturing can be optimally combined. The chatbot has the task to identify further fields of application for additive manufacturing, minimize problems and errors and optimize assembly processes.
In addition, the chatbot should be trained with specific data on additive manufacturing to select the appropriate process, including material, for the respective quality problems. Based on the current analysis and the evaluation of the quality data by using the chatbot, the appropriate of the different additive manufacturing processes can be ensured and other erases can be validated.
Date of Award2024
Original languageGerman (Austria)
SupervisorHolger Gröning (Supervisor)

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