scholarly journals Physics-Based Predictive Model of Lack-of-Fusion Porosity in Laser Powder Bed Fusion Considering Cap Area

Crystals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1568
Author(s):  
Wenjia Wang ◽  
Steven Y. Liang
Keyword(s):  
Image Analysis ◽  
Cross Section ◽  
Void Fraction ◽  
Material Properties ◽  
Molten Pool ◽  
Analytical Modeling ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Lack Of Fusion

This work proposed a computationally efficient analytical modeling strategy to calculate the product porosity in laser powder bed fusion (LPBF) induced by a lack-of-fusion defect, with the consideration of cap area in solidified molten pools, influence of powder bed characteristics on material properties, and un-melted powders in the lack-of-fusion portion. The powder packing pattern and powder bed void fraction were estimated by an advancing front method and the technique of image analysis. The effects of powder bed characteristics on the material properties were considered by analytical models with solid properties and powder bed void fraction as inputs. A physics-based thermal model was utilized to calculate the temperature distribution and molten pool size. The molten pool cross section in transvers direction was assumed to be dual half-elliptical. Based on this assumption and molten pool size, the geometry of the molten pool cross section with cap area was determined. The overlapping pattern of molten pools in adjacent scan tracks and layers was then obtained with given hatch space and layer thickness. The lack-of-fusion area fraction was obtained through image analysis of the overlapping pattern. The lack-of-fusion porosity was the multiplication of the lack-of-fusion area fraction and powder bed void fraction. The predictions of porosity under different process conditions were compared with experimental results of 316L stainless steel and showed a better predictive accuracy than the predictions that did not consider cap area. The proposed analytical modeling method has no numerical calculations, which ensures its low computational cost. Thus, the proposed model can be a convenient tool for the fast computation of lack-of-fusion-induced porosity and can help the quality control in LPBF.

Evaluation of the Material Properties of the Ti and CoCr Alloys Prepared by Laser Powder Bed Fusion

2020 ◽  
Vol 985 ◽  
pp. 223-228
Author(s):  
Jana Bidulská ◽  
Róbert Bidulský ◽  
Patrik Petrouse ◽  
Tibor Kvačkaj ◽  
Marco Actis Grande ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Image Analysis ◽  
Additive Manufacturing ◽  
Material Properties ◽  
Ti6al4v Alloy ◽  
Homogeneous Distribution ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Quantitative Image

The main aim of the present paper is evaluated the mechanical properties, microstructures and porosity of Ti6Al4V and CoCrW alloys produced by Laser Powder Bed Fusion (L-PBF) as an additive manufacturing (AM) technology. The mechanical properties were follows: For Ti6Al4V alloy the UTS was 1180 MPa; the YS was in the range <600; 745 MPa>. For CoCrW alloys, the UTS were in range <750; 950 MPa> and YS was in range <400; 500>. Evaluation of porosity was realized on non-etched samples using by quantitative image analysis in order to describe the dimensional and morphological porosity characteristics. The pores in the Ti6Al4V alloy showed homogeneous distribution without significant large pores.

scholarly journals Analytical Prediction of Balling, Lack-of-Fusion and Keyholing Thresholds in Powder Bed Fusion

2021 ◽  
Vol 11 (24) ◽  
pp. 12053
Author(s):  
Wenjia Wang ◽  
Jinqiang Ning ◽  
Steven Y. Liang
Keyword(s):  
Molten Pool ◽  
Laser Power ◽  
Computational Time ◽  
Process Conditions ◽  
Analytical Prediction ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Lack Of Fusion ◽  
Analytical Thermal Model

This paper proposes analytical modeling methods for the prediction of balling, lack-of-fusion and keyholing thresholds in the laser powder bed fusion (LPBF) additive manufacturing. The molten pool dimensions were first predicted by a closed-form analytical thermal model. The effects of laser power input, boundary heat loss, powder size distribution and powder packing pattern were considered in the calculation process. The predicted molten pool dimensions were then employed in the calculation of analytical thresholds for these defects. Reported experimental data with different materials were compared to predictions to validate the presented analytical models. The predicted thresholds of these defects under various process conditions have good agreement with the experimental results. The computation time for the presented models is less than 5 min on a personal computer. The optimized process window for Ti6Al4V was obtained based on the analytical predictions of these defects. The sensitivity analyses of the value of threshold to the laser power and scanning speed were also conducted. The proposed analytical methods show higher computational efficiency than finite element methods, without including any iteration-based computations. The acceptable predictive accuracy and low computational time will make the proposed analytical strategy be a good tool for the optimization of process conditions for the fabrication of defects-free complex products in laser powder bed fusion.

scholarly journals Effects of Positioning Conditions on Material Properties In Powder bed Fusion Additive Manufacturing

2021 ◽  
Author(s):  
Mevlüt Yunus Kayacan ◽  
Nihat Yılmaz
Keyword(s):  
Additive Manufacturing ◽  
Material Properties ◽  
Layer By Layer ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Cooling Rates ◽  
Powder Bed ◽  
Manufacturing Technologies ◽  
Average Size ◽  
Hardness Values

Abstract Among additive manufacturing technologies, Laser Powder Bed Fusion (L-PBF) is considered the most widespread layer-by-layer process. Although the L-PBF, which is also called as SLM method, has many advantages, several challenging problems must be overcome, including part positioning issues. In this study, the effect of part positioning on the microstructure of the part in the L-PBF method was investigated. Five Ti6Al4V samples were printed in different positions on the building platform and investigated with the aid of temperature, porosity, microstructure and hardness evaluations. In this study, martensitic needles were detected within the microstructure of Ti6Al4V samples. Furthermore, some twins were noticed on primary martensitic lines and the agglomeration of β precipitates was observed in vanadium rich areas. The positioning conditions of samples were revealed to have a strong effect on temperature gradients and on the average size of martensitic lines. Besides, different hardness values were attained depending on sample positioning conditions. As a major result, cooling rates were found related to positions of samples and the location of point on the samples. Higher cooling rates and repetitive cooling cycles resulted in microstructures becoming finer and harder.

Residual Stress Measurements in a 316L Uniaxial Samples Manufactured by Laser Powder Bed Fusion

2020 ◽  
Author(s):  
C. M. Davies ◽  
P. Sandmann ◽  
T. Ronneberg ◽  
P. A. Hooper ◽  
Saurabh Kabra
Keyword(s):  
Residual Stress ◽  
Residual Stresses ◽  
Cross Section ◽  
316L Stainless Steel ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Stress Measurements ◽  
Compressive Stresses ◽  
Central Cross Section

Abstract Uniaxial samples have been manufactured for tension/compression testing from 316L stainless steel by laser powder bed fusion (LPBF). Samples manufactured by LPBF are known to contain high levels of residual stresses. These uniaxial samples were built from a solid cylindrical rod and subsequently machined to reduce the central cross section of the sample to the required gauge diameter and improve the surface finish. Finite element (FE) models have been developed to simulate the LPBF process of the rods, their removal from the build plate and subsequent machining into the tension/compression samples. High tensile residual stresses were predicted at the surface of the samples, balances by similar magnitude compressive stresses along their axis. Post machining however, these stresses were reduced by around 80% or more. Residual stress measurements were performed on the samples post machining using the neutron diffraction techniques. These measurements confirmed that negligible residual stresses remained in the samples post removal from the build plate and machining.

Characterization of channels made by laser powder bed fusion and binder jetting using X-ray CT and image analysis

2020 ◽  
Vol 36 ◽  
pp. 101445
Author(s):  
T. Dahmen ◽  
C.G. Klingaa ◽  
S. Baier-Stegmaier ◽  
A. Lapina ◽  
D.B. Pedersen ◽  
...  
Keyword(s):  
Image Analysis ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
X Ray ◽  
Binder Jetting

Process Mapping and In-Process Monitoring of Porosity in Laser Powder Bed Fusion Using Layerwise Optical Imaging

2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Farhad Imani ◽  
Aniruddha Gaikwad ◽  
Mohammad Montazeri ◽  
Prahalada Rao ◽  
Hui Yang ◽  
...  
Keyword(s):  
Process Parameters ◽  
Process Conditions ◽  
Layer By Layer ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Graph Theoretic ◽  
Lack Of Fusion ◽  
Spectral Graph ◽  
Optical Images

The goal of this work is to understand the effect of process conditions on lack of fusion porosity in parts made using laser powder bed fusion (LPBF) additive manufacturing (AM) process, and subsequently, to detect the onset of process conditions that lead to lack of fusion-related porosity from in-process sensor data. In pursuit of this goal, the objectives of this work are twofold: (1) quantify the count (number), size and location of pores as a function of three LPBF process parameters, namely, the hatch spacing (H), laser velocity (V), and laser power (P); and (2) monitor and identify process conditions that are liable to cause porosity through analysis of in-process layer-by-layer optical images of the build invoking multifractal and spectral graph theoretic features. These objectives are important because porosity has a significant impact on the functional integrity of LPBF parts, such as fatigue life. Furthermore, linking process conditions to defects via sensor signatures is the first step toward in-process quality assurance in LPBF. To achieve the first objective, titanium alloy (Ti–6Al–4V) test cylinders of 10 mm diameter × 25 mm height were built under differing H, V, and P settings on a commercial LPBF machine (EOS M280). The effect of these process parameters on count, size, and location of pores was quantified based on X-ray computed tomography (XCT) images. To achieve the second objective, layerwise optical images of the powder bed were acquired as the parts were being built. Spectral graph theoretic and multifractal features were extracted from the layer-by-layer images for each test part. Subsequently, these features were linked to the process parameters using machine learning approaches. Through these image-based features, process conditions under which the parts were built were identified with the statistical fidelity over 80% (F-score).

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