Design and Modeling of a Microscale Selective Laser Sintering System

Author(s):  
Nilabh Roy ◽  
Anil Yuksel ◽  
Michael Cullinan

The development of micro and nanoscale additive manufacturing methods in metals and ceramics is important for many applications in the aerospace, medical device, and electronics industries. Unfortunately, most commercially available metal additive manufacturing tools have feature-size resolutions of greater than 100 μm, which is too large to precisely control the microstructure of the parts they produce. A few research-grade metal additive manufacturing tools do exist, but their build rate is generally too slow for commercial applications. Therefore, this paper presents a new microscale selective laser sintering (μ-SLS) that can be used to improve the minimum feature-size resolution of metal additively manufactured parts by up to two orders of magnitude, while still maintaining the throughput of traditional additive manufacturing processes. In order to achieve this goal, several innovative design features like the use of (1) ultra-fast lasers, (2) a micro-mirror based optical system, (3) nanoscale powders, and (4) a precision spreader mechanism, have been implemented. The micro-SLS system is capable of achieving build rates of approximately 1 cm3/hr while achieving a feature-size resolution of approximately 1 μm. This paper will also present new molecular scale models that have been developed for the micro-SLS to quantify and certify the micro-SLS build process. Modeling of the micro-SLS process is challenging, because most macroscale models of the SLS process contain assumptions that are no longer valid when the size of the particles that are being sintered is smaller than the wavelength of the laser being used to sinter them. Therefore, in modeling the micro-SLS process we must account for the wave nature of light and can no longer rely on the ray tracing models commonly used to model the SLS process. Also, heat transfer in the micro-SLS process is dominated by near-field radiation due to the diffraction of the light off the nanoparticles in the powder bed and the ultrafast lasers that are used in the micro-SLS system. This means that the assumptions of heat transfer by conduction and far-field radiation in the macroscale SLS systems are no longer valid for the micro-SLS system. Finally, the agglomeration of nanoparticles in the powder bed must be accurately modeled in order to precisely predict the formation of defects in the final parts produced. Overall, the goal of this modeling effort is to be able to predict the quality of a part produced using any given processing conditions, in order to produce parts that are “born certified” and do not need to be tested post fabrication.

Materials ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1988 ◽  
Author(s):  
Jinqiang Ning ◽  
Wenjia Wang ◽  
Xuan Ning ◽  
Daniel E. Sievers ◽  
Hamid Garmestani ◽  
...  

This work presents a computationally efficient predictive model based on solid heat transfer for temperature profiles in powder bed metal additive manufacturing (PBMAM) considering the heat transfer boundary condition and powder material properties. A point moving heat source model is used for the three-dimensional temperature prediction in an absolute coordinate. The heat loss from convection and radiation is calculated using a heat sink solution with a mathematically discretized boundary considering non-uniform temperatures and heat loss at the boundary. Powder material properties are calculated considering powder size statistical distribution and powder packing. The spatially uniform and temperature-independent material properties are employed in the temperature prediction. The presented model was tested in PBMAM of AlSi10Mg under different process conditions. The calculations of material properties are needed for AlSi10Mg because of the significant difference in thermal conductivity between powder form and solid bulk form. Close agreement is observed upon experimental validation on the molten pool dimensions.


2020 ◽  
Vol 2020 (0) ◽  
pp. S04110
Author(s):  
Kenya YUASA ◽  
Masaharu TAGAMI ◽  
Makiko YONEHARA ◽  
Toshi-Taka IKESHOJI ◽  
Koki TAKESHITA ◽  
...  

2018 ◽  
Vol 32 ◽  
pp. 744-753 ◽  
Author(s):  
Bo Cheng ◽  
James Lydon ◽  
Kenneth Cooper ◽  
Vernon Cole ◽  
Paul Northrop ◽  
...  

Author(s):  
Elham Mirkoohi ◽  
Daniel E. Sievers ◽  
Steven Y. Liang

Abstract A physics-based analytical solution is proposed in order to investigate the effect of hatch spacing and time spacing (which is the time delay between two consecutive irradiations) on thermal material properties and melt pool geometry in metal additive manufacturing processes. A three-dimensional moving point heat source approach is used in order to predict the thermal behavior of the material in additive manufacturing process. The thermal material properties are considered to be temperature dependent since the existence of the steep temperature gradient has a substantial influence on the magnitude of the thermal conductivity and specific heat, and as a result, it has an influence on the heat transfer mechanisms. Moreover, the melting/solidification phase change is considered using the modified heat capacity since it has an influence on melt pool geometry. The proposed analytical model also considers the multi-layer aspect of metal additive manufacturing since the thermal interaction of the successive layers has an influence on heat transfer mechanisms. Temperature modeling in metal additive manufacturing is one of the most important predictions since the presence of the temperature gradient inside the build part affect the melt pool size and geometry, thermal stress, residual stress, and part distortion. In this paper, the effect of time spacing and hatch spacing on thermal material properties and melt pool geometry is investigated. Both factors are found statistically significant with regard to their influence on thermal material properties and melt pool geometry. The predicted melt pool size is compared to experimental values from independent reports. Good agreement is achieved between the proposed physics-based analytical model and experimental values.


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