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@PHDTHESIS{Horstkotte:1009810,
author = {Horstkotte, Rainer},
othercontributors = {Bergs, Thomas and Schleifenbaum, Johannes Henrich},
title = {{M}ethodik zur {A}utomatisierung der additiven
{P}rozesskette mit {P}ulverbettverfahren; 1. {A}uflage},
volume = {2025,1},
school = {RWTH Aachen University},
type = {Dissertation},
address = {Aachen},
publisher = {Apprimus Verlag},
reportid = {RWTH-2025-03685},
isbn = {978-3-98555-258-0},
series = {Innovations in manufacturing technology},
pages = {1 Online-Ressource : Illustrationen},
year = {2025},
note = {Druckausgabe: 2025. - Auch veröffentlicht auf dem
Publikationsserver der RWTH Aachen University; Dissertation,
RWTH Aachen University, 2024},
abstract = {Additive manufacturing is gaining acceptance in industry as
a powerful technology for producing complex products. In
particular, powder bed-based manufacturing processes such as
Laser Powder Bed Fusion (LPBF) are highly relevant to
industry. The mechanical properties of additively
manufactured parts are comparable to those of conventional
manufacturing processes, but additional process steps are
required for further processing. According to the current
state, the additive manufacturing process itself and the
further processing steps are largely automated. However, the
non-value-adding activities in particular require a high
proportion of manual work. Within the scope of this
dissertation, a methodology for the automation of the
additive process chain was developed, which addresses both
manufacturing technology and economic objectives. Based on
requirements from research and industry, the methodology
consists of four consecutive phases. The goal of the first
phase is to create a data base by systematically gathering
available information about the component portfolio, the
process chain, and the existing production equipment and
peripheral systems, and to determine the degree of
automation. In the generation phase, a mathematical
optimization model is used to generate various automation
concepts based on algorithms, which are then specified in
terms of production technology. The third phase of the
methodology is the detailing phase, which is used to
quantify manufacturing and economic key performance
indicators. A material flow simulation is used to determine
the resulting lead times and other indicators for predicting
production capacity for different concepts. Finally, the
selection phase is used for the final determination of the
automation concept based on individual target criteria. The
methodology developed in this dissertation for the
automation of the additive process chain with powder bed
processes is the first holistic approach for the
cross-technology generation and evaluation of automation
concepts. Its applicability is particularly high due to the
prototypical software implementations. Companies with an
additive process chain are enabled to develop automation
concepts according to their requirements, to detail them in
terms of key performance indicators and finally to select
the optimal concept.},
cin = {417410 / 053200 / 417400},
ddc = {620},
cid = {$I:(DE-82)417410_20140620$ / $I:(DE-82)053200_20140620$ /
$I:(DE-82)417400_20240301$},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
doi = {10.18154/RWTH-2025-03685},
url = {https://publications.rwth-aachen.de/record/1009810},
}
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