Qualitätsorientierte modellbasierte Prozessparameteroptimierung für das Fused Deposition Modeling
Fuhrmann, Marco Heinrich; Schmitt, Robert Heinrich (Thesis advisor); Schleifenbaum, Johannes Henrich (Thesis advisor)
1. Auflage. - Aachen : Apprimus Verlag (2018)
Book, Dissertation / PhD Thesis
In: Ergebnisse aus der Produktionstechnik 23/2018
Page(s)/Article-Nr.: 1 Online-Ressource (ix, 1, 162 Seiten) : Illustrationen
Additive manufacturing technologies (3D printing) revolutionize production technology by enabling the individual production of goods in batch size 1. Because of the low investment inhibition threshold, particularly 3D printers in the low and medium budget segment are very interesting especially for SME’s. These desktop 3D printers, which are often based on fused deposition modeling technology, are in many cases not able to achieve a consistently high product quality. The subject of this thesis is therefore the quality-oriented model-based process parameter optimization for the fused deposition modeling. The situation-dependent and flexible optimal setting of the process parameters is a central task for the realization of quality-optimized production systems. The main idea of the presented solution is to implement an application-specific combination of black box and white box models for a new grey box approach for several target variables, which allow the optimal parameter setting and adapt to changing conditions, such as new component geometries. Based on the analysis of the object areas optimization, modelling and additive manufacturing processes, the scope of the work is limited and the state of the art for the model-based optimization of additive manufacturing processes is specified. The resulting research gaps and consequently, the corresponding research questions are derived. Subsequently, different models are developed for the FDM technology for a total of four variables with eight target factors. Black box models based on empirical data obtained from experiments of a statistical experimental design as well as white box models, which are derived on the basis of literature review and own considerations. These models are validated and combined to a grey box approach for each target value. The generated models are implemented in a simulation environment together with a suitable minimization algorithm and the entire concept is subsequently validated. Finally, the approach is generalized and thus, a procedure for the grey box modeling for complex technologies is derived. The result is, on the one hand, a simulation environment with user interface for an exemplary FDM process and, on the other hand, a general approach, how the parameter optimization can be realized using grey box models for complex technologies. The simulation environment allows a user to predict the target variables based on defined parameter settings and also the optimization of these target variables by means of the optimization algorithm and the grey box models. The models adapt automatically to changing conditions and applications when new data is available. Furthermore, the developed general approach can be implemented for various complex technologies.