Browsing by Author "Faria, S."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
- Predictive models for physical and mechanical properties of 316L stainless steel produced by selective laser meltingPublication . Miranda, G.; Faria, S.; Bartolomeu, F.; Pinto, Elodie; Madeira, S.; Mateus, Artur; P.Carreira; Alves, Nuno; Silva, F.S.; Carvalho, O.Selective Laser Melting (SLM) processing parameters are known to greatly influence 316L stainless steel final properties. A simple energy density calculation is insufficient for explaining mechanical and physical properties as well as microstructural characteristics, which are known to significantly influence these parts performance. In fact, parts produced by using different combinations of processing parameters, even presenting similar energy density, can display different properties. Thus, it is necessary to assess their influence as isolated parameters but also their interactions. This work presents a study on the influence of several SLM processing parameters (laser power, scanning speed and scanning spacing) on density, hardness and shear strength of 316L stainless steel. The influence of these processing parameters on the abovementioned properties is assessed by using statistical analysis. In order to find the significant main factors and their interactions, analysis of variance (ANOVA) is used. Furthermore, in order to assess the effect of the part building orientation, two different building strategies were tested. The influence of these processing parameters on shear strength, hardness and density were assessed for the two building strategies, thus resulting six different models that can be used as predictive design tools. The microstructures experimentally obtained were analyzed, discussed and correlated with the obtained models.
- Predictive models for physical and mechanical properties of Ti6Al4V produced by Selective Laser MeltingPublication . Bartolomeu, F.; Faria, S.; Carvalho, O.; Pinto, E.; Alves, Nuno; Silva, F.S.; Miranda, G.The properties of parts produced by Selective Laser Melting (SLM) are highly influenced by the processing parameters. The calculation of the energy density is not enough for justifying the mechanical and physical properties, and understand the microstructures of Ti6Al4V samples produced by SLM. In fact, samples produced with the same energy density, but with different processing parameters, present distinct properties. In this sense, it is necessary to assess the influence of processing parameters on SLM fabrication, as isolated parameters but also their interactions. This work presents a study on the influence of several SLM processing parameters (laser power, scan speed and scan spacing) on density, hardness and shear strength of Ti6Al4V samples. The influence of these processing parameters on the final properties of SLM parts was obtained by using statistical analysis. Additionality, with the drive of finding the significant main factors and their interactions, analysis of variance (ANOVA) was performed. The influence of the above mentioned processing parameters on shear strength, hardness and density resulted in three models that can be used as predictive design tools for Ti6Al4V parts produced by SLM technology. Moreover, a study on the microstructures of the Ti6Al4V samples was performed and correlated with the obtained models.
- A study on the production of thin-walled Ti6Al4V parts by selective laser meltingPublication . Miranda, G.; Faria, S.; Bartolomeu, F.; Pinto, E.; Alves, N.; Peixinho, N.; Gasik, M.; Silva, F.S.Selective Laser Melting (SLM) is an extremely versatile technology especially suited for the manufacturing of thin-walled parts. Micro-sized parts are highly influenced and dependent on the SLM processing parameters; thus being indispensable to assess the influence of processing parameters on SLM fabrication, as isolated parameters but also their interactions. In this study, the influence of SLM laser power and scanning speed on Ti6Al4V micropillars and micro-plates thickness was assessed by applying response surface methodology (RSM). These analyses resulted in four models that exhibit complex correlations of SLM process parameters, with non-linear equations, having coefficients of determination that assess the quality of the models. These developed models are accurate tools that can be used to optimize the micro manufacture of Ti6Al4V thin-walled parts by SLM.