Investigation of material characteristics of intersections built by wire and arc additive manufacturing using locally varying deposition parameters

2021 ◽  
Author(s):  
Manuela Gudeljevic ◽  
Thomas Klein
Keyword(s):  
Additive Manufacturing ◽  
Material Characteristics ◽  
Deposition Parameters

scholarly journals Processing Conditions of a Medical Grade Poly(Methyl Methacrylate) with the Arburg Plastic Freeforming Additive Manufacturing Process

Polymers ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2677
Author(s):  
Lukas Hentschel ◽  
Frank Kynast ◽  
Sandra Petersmann ◽  
Clemens Holzer ◽  
Joamin Gonzalez-Gutierrez
Keyword(s):  
Additive Manufacturing ◽  
Methyl Methacrylate ◽  
Tensile Properties ◽  
Discharge Rate ◽  
Processing Conditions ◽  
Poly Methyl Methacrylate ◽  
Geometrical Accuracy ◽  
Deposition Parameters ◽  
Chamber Temperature ◽  
Medical Grade

The Arburg Plastic Freeforming process (APF) is a unique additive manufacturing material jetting method. In APF, a thermoplastic material is supplied as pellets, melted and selectively deposited as droplets, enabling the use of commercial materials in their original shape instead of filaments. The medical industry could significantly benefit from the use of additive manufacturing for the onsite fabrication of customized medical aids and therapeutic devices in a fast and economical way. In the medical field, the utilized materials need to be certified for such applications and cannot be altered in any way to make them printable, because modifications annul the certification. Therefore, it is necessary to modify the processing conditions rather than the materials for successful printing. In this research, a medical-grade poly(methyl methacrylate) was analyzed. The deposition parameters were kept constant, while the drop aspect ratio, discharge rate, melt temperatures, and build chamber temperature were varied to obtain specimens with different geometrical accuracy. Once satisfactory geometrical accuracy was obtained, tensile properties of specimens printed individually or in batches of five were tested in two different orientations. It was found that parts printed individually with an XY orientation showed the highest tensile properties; however, there is still room for improvement by optimizing the processing conditions to maximize the mechanical strength of printed specimens.

Polyvinylidene fluoride (PVDF) as a feedstock for material extrusion additive manufacturing

2020 ◽  
Vol 26 (1) ◽  
pp. 156-163 ◽  
Author(s):  
Niknam Momenzadeh ◽  
Hadi Miyanaji ◽  
Daniel Allen Porter ◽  
Thomas Austin Berfield
Keyword(s):  
Additive Manufacturing ◽  
Polyvinylidene Fluoride ◽  
Mechanical Response ◽  
Dimensional Accuracy ◽  
Piezoelectric Response ◽  
Content Type ◽  
Material Extrusion ◽  
Deposition Parameters ◽  
The Individual ◽  
Deposition Conditions

Purpose This study aims to investigate the material extrusion additive manufacturing (MEAM) deposition parameters for creating viable 3-D printed polyvinylidene fluoride (PVDF) structures with a balanced mix of mechanical and electrical properties. Design/methodology/approach Different combinations of deposition conditions are tested, and the influence of these parameters on the final dimensional accuracy, semi-crystalline phase microstructure and effective mechanical strength of MEAM homopolymer PVDF printed parts is experimentally assessed. Considering printed part integrity, appearance, print time and dimensional accuracy, MEAM parameters for PVDF are suggested. Findings A range of viable printing parameters for MEAM fabricated PVDF Kynar 740 objects of different heights and in-plane length dimensions was determined. For PVDF structures printed under the suggested conditions, the mechanical response and the microstructure development related to Piezoelectric response are reported. Originality/value This research first reports on a range of parameters that have been confirmed to facilitate effective MEAM printing of 3-D PVDF objects, presents effects of the individual parameters and gives the mechanical and microstructure properties of PVDF structures fabricated under the suggested deposition conditions.

scholarly journals Additive Manufacturing of H11 with Wire-Based Laser Metal Deposition

2017 ◽  
Vol 22 (4) ◽  
pp. 466-479 ◽  
Author(s):  
Stella Holzbach Oliari ◽  
Ana Sofia Clímaco Monteiro D’Oliveira ◽  
Martin Schulz
Keyword(s):  
Additive Manufacturing ◽  
Travel Speed ◽  
Metal Deposition ◽  
Parameters Optimization ◽  
Layer By Layer ◽  
Laser Metal Deposition ◽  
3D Cad ◽  
Deposition Parameters ◽  
Commercial Applications ◽  
Functional Components

Abstract Laser additive manufacturing (LAM) is a near-net-shape production technique by which a part can be built up from 3D CAD model data, without material removal. Recently, these production processes gained attention due to the spreading of polymer-based processes in private and commercial applications. However, due to the insufficient development of metal producing processes regarding design, process information and qualification, resistance on producing functional components with this technology is still present. To overcome this restriction further studies have to be undertaken. The present research proposes a parametric study of additive manufacturing of hot work tool steel, H11. The selected LAM process is wire-based laser metal deposition (LMD-W). The study consists of parameters optimization for single beads (laser power, travel speed and wire feed rate) as well as lateral and vertical overlap for layer-by-layer technique involved in LMD process. Results show that selection of an ideal set of parameters affects substantially the surface quality, bead uniformity and bond between substrate and clad. Discussion includes the role of overlapping on the soundness of parts based on the height homogeneity of each layer, porosity and the presence of gaps. For the conditions tested it was shown that once the deposition parameters are selected, lateral and vertical overlapping determines the integrity and quality of parts processed by LAM.

scholarly journals Bead Geometry Prediction in Laser-Wire Additive Manufacturing Process Using Machine Learning: Case of Study

2021 ◽  
Vol 11 (24) ◽  
pp. 11949
Author(s):  
Natago Guilé Mbodj ◽  
Mohammad Abuabiah ◽  
Peter Plapper ◽  
Maxime El Kandaoui ◽  
Slah Yaacoubi
Keyword(s):  
Machine Learning ◽  
Additive Manufacturing ◽  
Prediction Model ◽  
Travel Speed ◽  
Bead Geometry ◽  
Layer By Layer ◽  
Evolutionary Trend ◽  
Deposition Parameters ◽  
Layer Deposition ◽  
Height Prediction

In Laser Wire Additive Manufacturing (LWAM), the final geometry is produced using the layer-by-layer deposition (beads principle). To achieve good geometrical accuracy in the final product, proper implementation of the bead geometry is essential. For this reason, the paper focuses on this process and proposes a layer geometry (width and height) prediction model to improve deposition accuracy. More specifically, a machine learning regression algorithm is applied on several experimental data to predict the bead geometry across layers. Furthermore, a neural network-based approach was used to study the influence of different deposition parameters, namely laser power, wire-feed rate and travel speed on bead geometry. To validate the effectiveness of the proposed approach, a test split validation strategy was applied to train and validate the machine learning models. The results show a particular evolutionary trend and confirm that the process parameters have a direct influence on the bead geometry, and so, too, on the final part. Several deposition parameters have been found to obtain an accurate prediction model with low errors and good layer deposition. Finally, this study indicates that the machine learning approach can efficiently be used to predict the bead geometry and could help later in designing a proper controller in the LWAM process.

scholarly journals Effect of clad height, substrate thickness and scanning pattern on cantilever distortion in direct metal deposition

2021 ◽  
Author(s):  
Fabian Soffel ◽  
Daniel Eisenbarth ◽  
Konrad Wegener
Keyword(s):  
Additive Manufacturing ◽  
Dimensional Accuracy ◽  
Industrial Applications ◽  
Substrate Thickness ◽  
Experimental Conditions ◽  
Shape Accuracy ◽  
Experimental Calibration ◽  
Scanning Pattern ◽  
Deposition Parameters ◽  
Layer Deposition

AbstractIn metal additive manufacturing, moving heat sources cause spatial and time-dependent variations of temperature and strain that can lead to part distortions. Distortion prediction and optimized deposition parameters can increase the dimensional accuracy of the generated components. In this study, an analytical approach for modeling the effect of clad height and substrate thickness is experimentally validated. Additionally, the influence of the scanning pattern as a function of clad height and substrate thickness is determined experimentally. The analytical model is based on the cool-down phase mechanism and assumes the formation of constant thermal shrinking forces for each deposited layer. The model accurately predicts longitudinal cantilever distortion after experimental calibration when compared with similar experimental conditions. For multi-layer deposition, the scanning pattern has the largest influence on distortion for thin-walled substrates. An optimized deposition strategy with longitudinal scanning vectors leads to a distortion reduction of up to 86%. The results highlight the potential of mechanical modeling and scanning strategy optimizations to increase the shape accuracy for industrial applications in the field of additive manufacturing.

scholarly journals Orientation Effects on Fatigue Behavior of Additively Manufactured Stainless Steel

2017 ◽  
Author(s):  
Thale R. Smith ◽  
Joshua D. Sugar ◽  
Chris San Marchi ◽  
Julie M. Schoenung
Keyword(s):  
Stainless Steel ◽  
Additive Manufacturing ◽  
Fatigue Testing ◽  
Fatigue Behavior ◽  
Build Orientation ◽  
Design Flexibility ◽  
Deposition Parameters ◽  
Design Choice ◽  
Direct Energy ◽  
Near Net Shape

Direct energy deposition (DED) is an additive manufacturing process that can produce complex near-net shape metallic components in a single manufacturing step. DED additive manufacturing has the potential to reduce feedstock material waste, streamline manufacturing chains, and enhance design flexibility. A major impediment to broader acceptance of DED technology is limited understanding of defect populations in the novel microstructures produced by DED and their relationship to process parameters and resultant mechanical properties. A design choice as simple as changing the build orientation has been observed to result in differences as great as ∼25% in yield strength for type 304L austenitic stainless steel deposited with otherwise identical deposition parameters. To better understand the role of build orientation and resultant defect populations on fatigue behavior in DED 304L, tension-tension fatigue testing has been performed on circumferentially notched cylindrical test specimens extracted from both vertical and horizontal orientations relative to the build direction. Notched fatigue behavior was found to be strongly influenced by the manufacturing defect populations of the material for different build orientations.

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