scholarly journals Experimental investigations for improved modelling of the laser sintering process of polymers

Procedia CIRP ◽  
2020 ◽  
Vol 94 ◽  
pp. 80-84 ◽  
Author(s):  
Johannes Rudloff ◽  
Marieluise Lang ◽  
Shoya Mohseni-Mofidi ◽  
Claas Bierwisch
2016 ◽  
Vol 22 (2) ◽  
pp. 405-415 ◽  
Author(s):  
Alkhair Almabrouk Mousa

Purpose This paper aims to investigate the curling behaviour of selective laser sintered polyamide/glass bead composites with changes in material compositions, part bed temperature, powder base thickness, laser power and layer cooling time. Design/methodology/approach The Taguchi parameter design method (design of experiments, DOE) and analysis of variance (ANOVA) technique were applied in the investigation to determine the optimal process parameter settings. Findings The results of statistical analysis and ANOVA provided evidence for the effectiveness of filler content and its surface treatment on reducing the amount of curling. Research limitations/implications Warping and curling phenomena is one of several aspects of this work that can be pursued further. The present investigation could be expanded to explore other fillers and interface adhesion using other modifiers. Experiments could be conducted with other complicated geometries, various sizes, different positions and locations to widen the knowledge base of geometric accuracy of selective laser sintering process. Practical implications This experimental work is beneficial for materials development and accuracy characterisation in rapid manufacturing techniques. The experimental techniques adopted are readily transferable to virtually any material system used in rapid manufacturing. Originality/value Although many materials have been developed, there is still a need for research into new materials. This work demonstrates that it is possible to improve the geometric accuracy of selective laser sintered components from glass bead- filled polyamide 12 and achieve near-zero curling by adding rigid multiphase-coated particle to the material system.


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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