@misc{GruegerFischerWolletal., author = {Gr{\"u}ger, Lennart and Fischer, Tim Sebastian and Woll, Ralf and Buhl, Johannes}, title = {Absicherung von Risiken beim Prozess des Wire Arc Additive Manufacturing}, series = {Industry 4.0 Science}, volume = {2024}, journal = {Industry 4.0 Science}, number = {1}, issn = {2942-6154}, doi = {10.30844/I4SD.24.1.63}, pages = {63 -- 69}, language = {de} } @incollection{GruegerFischerWoll, author = {Gr{\"u}ger, Lennart and Fischer, Tim Sebastian and Woll, Ralf}, title = {Investigation of the Wire Arc Direct Energy Deposition-Process and Possible Interactions}, series = {Advances in Manufacturing IV}, volume = {2024}, booktitle = {Advances in Manufacturing IV}, editor = {Gapiński, Bartosz and Ciszak, Olaf Stanisław and Ivanov, Vitalii and Machado, Jose Mendes}, edition = {4}, publisher = {Springer Nature Switzerland}, address = {Cham}, isbn = {9783031564659}, issn = {2195-4356}, doi = {10.1007/978-3-031-56463-5_14}, pages = {176 -- 194}, abstract = {The Wire Arc Direct Energy Deposition (WA-DED) process is highly regarded as part of additive manufacturing. Compared to other additive manufacturing processes, it is characterized above all by its high deposition rate and low system costs. Despite many years of experience in the build-up welding process, WA-DED still holds a number of challenges in terms of process stability. This article analyses the interactions in the WA-DED process. To this end, the process was visualized and described with the help of Structured Analysis and Design Technique (SADT). Building on this, a process Failure Mode and Effects Analysis (FMEA) was presented to identify and priorities risks. Finally, the results of the Taguchi tests were analyzed and visualized. The results illustrate the strong interactions between the influencing factors. These have a material-specific effect on the production results. Each new material composition therefore requires a systematic analysis in order to determine quantitative correlations. In future, these can be supported by machine learning approaches.}, language = {en} }