Investigation of FDM-Based 3D Printing for Optimized Tooling in Automotive and Electronics Sheet Metal Cutting
Source abstract
Abstract
Within the scope of the work, the possible use of fused deposition modeling (FDM) technology in executing rapid prototypes of cutting tools for aluminum sheets was systematically studied. Relevant investigations have thus far mainly concentrated on tools for the 3D printing of bent and deep-drawn pieces, yet the implementation of FDM tools in cutting has been insufficiently covered. This study aims to determine the characteristics of FDM cutting tools, such as wear and tear, dimensional stability, and cutting efficiency. Various tool designs were tested under different wall thicknesses and orientations with respect to the feed of Al99.5 sheets with thicknesses of 0.22 mm and 0.3 mm. According to the results, in the best case, three-dimensional printed PLA tools performed six cuts with no burrs and an acceptable wear level due to the IT tolerances (IT9 and IT10). Tools with thicker walls and more appropriate orientations were found to be more robust. However, some designs failed when subjected to greater loads, revealing a deficiency in some of the strength properties of the material. These observations suggest that it is possible to create 3D printed tools for modeling and small-scale production at considerably cheaper and faster rates than conventional methods. Future work will integrate advanced materials and designs to enhance tool performance, further solidifying FDM as a transformative approach in industrial tool manufacturing. With this research, the authors wanted to demonstrate that FDM technology can also be used to produce a classic sheet cut, which, of course, is still of great importance for prototyping or setting up production processes. This research demonstrated that FDM printing can play a role in this area.
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Research context
OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · Additive Manufacturing Materials and Processes · Manufacturing Process and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Central Campus Győr, Széchenyi István University, H-9026 Győr, Hungary
Department of Transport Infrastructure, Ukrainian State University of Science and Technologies, UA-49005 Dnipro, Ukraine
Department of Planning and Design of Railway Infrastructure, Technical University Dresden, D-01069 Dresden, Germany
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