## 6 Conclusions and Outlook  
In this contribution, a methodology for the statistical tolerance analysis of additively manufactured non-assembly mechanisms using empirical predictive models was presented. Since the current state-of-the-art concerning statistical tolerance analysis lacks in providing suitable methods for the consideration of comparatively large joint clearances and part deviations resulting from the AM process, this contributions thus closes this gap by the integration of predictive models and MBS. The application to an additively manufactured 8-bar mechanism has shown the general applicability of the methodology and the benefit of analysing its motion behaviour based on the chosen process parameters. It can be stated that the proposed methodology is suitable for evaluating the functionality of additively manufactured non-assembly mechanisms before fabrication. With the help of predictive models and MBS, the deviation from the desired coupling curve can be calculated, whereby the influence of geometric deviations and large joint clearances resulting from the FDM process depending on the choice of process parameters can be considered more precisely. Thus, this contribution provides less AM-experienced engineers with a methodology to evaluate and optimise their design and choose suitable process parameters before fabrication.  
Ongoing research activities will focus on the experimental validation of the presented methodology. Therefore, the motion behaviour of the presented 3D-printed non-assembly mechanism will be optically measured to determine its real motion behaviour and compare the results to the presented methodology. Subsequently, the general applicability of the presented methodology has to be checked, applying it to other AM-processes, e.g., SLA and SLM. Moreover, a future topic concerning the further improvement of non-assembly AM mechanisms for their use in industrial applications is the optimisation of process parameters. Therefore, a combination of ML techniques with a subsequent optimisation of the FDM-process parameters may be purposeful [23]. Other techniques in the pre-processing of the mechanisms, like adaptive slicing and non-planar printing are promising methods for the further improvement of the geometric accuracy of additively manufactured parts in general [46,47].  
Conceptualization, P.S., B.S. and S.W.; methodology, P.S.; software, P.S.; investigation, P.S.; writing--original draft preparation, S.P.; writing--review and editing, B.S. and S.W.; visualization, P.S.; supervision, B.S. and S.W.; project administration, S.W.; funding acquisition, S.W.; All authors have read and agreed to the published version of the manuscript.  
This research was funded by the German Research Foundation (DFG), grant number WA 2913/27-1.  
Not applicable.  
The authors thank the German Research Foundation (DFG) for supporting the research project \"Statistical tolerance analysis of linkage mechanisms taking into account deviations from additive manufacturing\" under the grant number WA 2913/27-1.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
ABS  
Acrylonitrile-butadiene-styrene  
Additive Manufacturing  
CoP  
Coefficient of prognosis  
DoE  
Design of experiment