Additive manufacturing processes are gaining increasing at-
tention in various gas cleaning applications since new process optimiza-
tions can be achieved (e.g. higher particle separation efficiency, lower
process energy consumption and less entrainment of secondary aerosol
into the clean gas).
When processing metals by grinding, brushing and polishing, submicron
metal particles as well as airborne liquid droplets (e.g. oil droplets) may
occur. These contaminants in the process air are undesired and need to
be separated from the gas stream. Hence, new technologies are aiming to
separate these submicron particles at a high particle separation efficiency
and a comparatively low pressure drop.
By utilizing additive manufacturing processes in gas cleaning applica-
tions, novel 3D-printed nozzle geometries for innovative wet separators
can be applied. Using those nozzles as pre-separator, the service life of
downstream filter elements can be extended.
Regarding the separation of airborne oil droplets from a gas stream,
high efficient coalescence filters are required. However, entrainment of
secondary aerosols into the clean gas may ruin the overall filtration effi-
ciency. Therefore, novel 3D-printed support structures on the filter down-
stream side are developed in order to reduce this secondary aerosol,
by applying drainage channels on the filter rear side to accelerate the
drainage of oil.
In this contribution the implementation of additive manufactured parts
in gas cleaning applications, exemplary for an innovative 3D-printed wet-
scrubber nozzle and novel 3D-printed support structures for oil mist fil-
ters, are presented.

Abstract. Additive manufacturing has been adopted across various in-
dustries to benefit from its unique capabilities. However, there is cur-
rently no significant use of the technology in the ultra-high vacuum in-
dustry. One challenge is the limited data available on the vacuum-specific
performance of laser powder bed fusion manufactured parts.
In this paper, the leak rate, outgassing, and residual gas analysis of
stainless steel 316L samples is evaluated, considering the as-built surface
and post-processing by glass bead blasting, Hirtisation, and machining.
Two of three machined samples showed a leak rate at the detection limit
of the test stand of 10−9 mbar L s−1. All samples showed a pump-down
behavior very similar to conventional stainless steel with all chamber
pressures within 1.4 × 10−8 mbar after 20 h of pumping. All surface post-
processed samples showed low levels of surface contamination, with the
ion currents above 50 amu more than three decades below the ion current
of H2O. The as-built samples with a machined surface were the only
samples to exceed this limit. Overall, while application-specific standards must be evaluated for each
use case, the results show the process to generally be ultra-high vacuum
compatible.

The purpose of this paper is to present propositions for facilitating the integration of additive manufacturing (AM) for manufacturing companies in the heavy vehicle sectors based on identified success factors and lessons learned in use cases with different operational purposes. A case study was conducted that identified 42 retrospective use cases from three main sources highlighting seven different use case types with contributions from seven sectors representing 14 countries on four continents. Six success factors (technology infrastructure, relative advantage, organizational readiness, competitive pressure, expectations of market trends, and trading partner) and 20 lessons learned sorted into five dimensions (additive thinking, management aspects, practice makes perfect, AM acceptance, and AM experts) were identified in the use cases based on the analysis. Three propositions covering the three stages of integration were derived based on the identified success factors and lessons learned. These propositions should provide guidance on what managers need to be prepared for when integrating AM step-by-step. Integrating AM is no simple feat, and the propositions only scratch the surface since the complexity of AM runs deep both technically and managerially. Future research should investigate in-depth operational capabilities and, if applicable, dynamic capabilities to further enhance facilitating the integration of AM step-by-step.