Development of an Empirical Model on Melt Pool Variation in Laser Foil Printing Additive Manufacturing Process Using Statistical Analysis

Author(s):  
M. Hossein Sehhat ◽  
Behrouz Behdani ◽  
Chia-Hung Hung ◽  
Ali Mahdianikhotbesara
Author(s):  
Bo Cheng ◽  
Kevin Chou

Powder-bed electron beam additive manufacturing has the potential to be a cost-effective alternative in producing complex-shaped, custom-designed metal parts using various alloys. Material thermal properties have a rather sophisticated effect on the thermal characteristics such as the melt pool geometry in fabrications, impacting the build part quality. The objective of this study is to achieve a quantitative relationship that can correlate the material thermal properties and the melt pool geometric characteristics in the electron beam additive manufacturing process. The motivation is to understand the interactions of material property effect since testing individual properties is insufficient because of the change of almost all thermal properties when switching from one to the other material. In this research, a full-factorial simulation experiment was conducted to include a wide range of the thermal properties and their combinations. A developed finite element thermal model was applied to perform electron beam additive manufacturing process thermal simulations incorporating tested thermal properties. The analysis of variance method was utilized to evaluate different thermal property effects on the simulated melt pool geometry. The major results are summarized as follows. (1) The material melting point is the most dominant factor to the melt pool size. (2) The role of the material thermal conductivity may outweigh the melting point and strongly affects the melt pool size, if the thermal conductivity is very high. (3) Regression equations to correlate the material properties and the melt pool dimension and shape have been established, and the regression-predicted results show a reasonable agreement with the simulation results for tested real-world materials. However, errors still exist for materials with a small melt pool such as copper.


2021 ◽  
Vol 1161 ◽  
pp. 137-144
Author(s):  
Jonas Holtmann ◽  
Denis Kiefel ◽  
Stefan Neumann ◽  
Rainer Stoessel ◽  
Christian U. Grosse

Process monitoring in additive manufacturing (AM), i.e. in laser powder bed fusion (LPBF) of metal parts, has been identified as the crucial bottleneck in accelerating the AM industrialization process. To reduce the cost and time needed to produce and qualify an AM part, an online monitoring system of the manufacturing process is desirable. While the currently available systems capture a large amount of process data, they still lack the ability to interpret the acquired data adequately. In this work we present the first steps towards an automated evaluation of online monitoring data i.e. melt pool data. It is shown that a well-trained convolutional neural network (CNN) is able to detect artificially induced process deviations on the basis of melt pool characteristics.


Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1547
Author(s):  
Syed Zahid Hussain ◽  
Zareena Kausar ◽  
Zafar Ullah Koreshi ◽  
Shakil R. Sheikh ◽  
Hafiz Zia Ur Rehman ◽  
...  

Selective laser melting (SLM), a metal powder fusion additive manufacturing process, has the potential to manufacture complex components for aerospace and biomedical implants. Large-scale adaptation of these technologies is hampered due to the presence of defects such as porosity and part distortion. Nonuniform melt pool size is a major cause of these defects. The melt pool size changes due to heat from the previous powder bed tracks. In this work, the effect of heat sourced from neighbouring tracks was modelled and feedback control was designed. The objective of control is to regulate the melt pool cross-sectional area rejecting the effect of heat from neighbouring tracks within a layer of the powder bed. The SLM process’s thermal model was developed using the energy balance of lumped melt pool volume. The disturbing heat from neighbouring tracks was modelled as the initial temperature of the melt pool. Combining the thermal model with disturbance model resulted in a nonlinear model describing melt pool evolution. The PID, a classical feedback control approach, was used to minimize the effect of intertrack disturbance on the melt pool area. The controller was tuned for the desired melt pool area in a known environment. Simulation results revealed that the proposed controller regulated the desired melt pool area during the scan of multiple tracks of a powder layer within 16 milliseconds and within a length of 0.04 mm reducing laser power by 10% approximately in five tracks. This reduced the chance of pore formation. Hence, it enhances the quality of components manufactured using the SLM process, reducing defects.


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