Development of industrial 3D real object duplication system by selective multi-laser sintering process

Author(s):  
DongSoo Kim ◽  
SungJong Kim
2014 ◽  
Vol 1038 ◽  
pp. 75-81
Author(s):  
Bernd Niese ◽  
Philipp Amend ◽  
Uwe Urmoneit ◽  
Stephan Roth ◽  
Michael Schmidt

Embedding stereolithography (eSLA) is an additive, hybrid process, which provides a flexible production of 3D components and the ability to integrate electrical and optical conductive structures and functional components within parts. However, the embedding of conductive circuits in stereolithography (SLA) parts assumes usage of process technologies, which enables their direct integration of conductive circuits during the layer-wise building process. In this context, a promising method for in-situ generation of conductive circuits is dispensing of conductive adhesive on the current surface of the SLA part and its subsequent sintering. In this paper, the laser sintering (λ = 355 nm) of conductive adhesive mainly consisting of silver nanoparticles is investigated. The work intends to evaluate the curing behavior of the conductive adhesive, the beam-matter-interactions and the thermal damage of the SLA substrate. The investigations revealed a fast and flexible laser sintering process for the generation of conductive circuits with sufficient electrical conductivity and sufficient current capacity load. In this context, a characterization of the conductive structures is done by measuring their electrical resistance and their potential current capacity load.


2017 ◽  
Vol 7 (5) ◽  
pp. 462 ◽  
Author(s):  
Manfred Schmid ◽  
Rob Kleijnen ◽  
Marc Vetterli ◽  
Konrad Wegener

2018 ◽  
Vol 8 (12) ◽  
pp. 2383 ◽  
Author(s):  
Zhehan Chen ◽  
Xianhui Zong ◽  
Jing Shi ◽  
Xiaohua Zhang

Selective laser sintering (SLS) is an additive manufacturing technology that can work with a variety of metal materials, and has been widely employed in many applications. The establishment of a data correlation model through the analysis of temperature field images is a recognized research method to realize the monitoring and quality control of the SLS process. In this paper, the key features of the temperature field in the process are extracted from three levels, and the mathematical model and data structure of the key features are constructed. Feature extraction, dimensional reduction, and parameter optimization are realized based on principal component analysis (PCA) and support vector machine (SVM), and the prediction model is built and optimized. Finally, the feasibility of the proposed algorithms and model is verified by experiments.


Author(s):  
Arash Gobal ◽  
Bahram Ravani

The process of selective laser sintering (SLS) involves selective heating and fusion of powdered material using a moving laser beam. Because of its complicated manufacturing process, physical modeling of the transformation from powder to final product in the SLS process is currently a challenge. Existing simulations of transient temperatures during this process are performed either using finite-element (FE) or discrete-element (DE) methods which are either inaccurate in representing the heat-affected zone (HAZ) or computationally expensive to be practical in large-scale industrial applications. In this work, a new computational model for physical modeling of the transient temperature of the powder bed during the SLS process is developed that combines the FE and the DE methods and accounts for the dynamic changes of particle contact areas in the HAZ. The results show significant improvements in computational efficiency over traditional DE simulations while maintaining the same level of accuracy.


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