Abstract
The design of additive manufacturing processes, especially for batch production in industrial practice, is of high importance for the propagation of new additive manufacturing technology. Manual redesign procedures of the additive manufactured parts based on discrete measurement data or numerical meshes are error prone and hardly automatable. To achieve the required final accuracy of the parts, often, various iterations are necessary. To address these issues, a data-driven geometrical compensation approach is proposed that adapts concepts from forming technology. The measurement information of a first calibration cycle of manufactured parts is the basis of the approach. Through non-rigid transformations of the part geometry, a new shape for the subsequent additive manufacturing process was derived in a systematic way. Based on a purely geometrical approach, the systematic portion of part deviations can be compensated. The proposed concept is presented first and was applied to a sample fin-shaped part. The deviation data of three manufacturing cycles was utilised for validation and verification.
Highlights
A central, key technology in the future will be additive manufacturing (AM) [1]
In AM, no tools are needed for manufacturing, but a manufacturing geometry has to be provided to the AM system. We proposed that this manufacturing geometry could be seen as a forming tool in a geometrical compensation sense
We further proposed that the displacement adjustment method, which directly incorporates the deviation data, is a suitable method for AM, because of its incremental characteristics
Summary
A central, key technology in the future will be additive manufacturing (AM) [1]. Opportunities are arising in combination with ongoing digitisation and cross-linking between production and design in line with industry 4.0. Central hurdles for the application in serial production are above all, the cost-related general conditions (high material costs in combination with an insufficient ratio of plant costs to productivity) and the high manual effort in the process chain due to the lack of physical and digital line integration. This current lack of the integration of AM processes in conventional production environments is due to the specifics of AM processes, such as batch production, and the currently low degree of automation in the peripheral systems, such as component handling, quality measurement and transport chains. In AM processes, deviations between the Technologies 2019, 7, 83; doi:10.3390/technologies7040083 www.mdpi.com/journal/technologies
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