Input: The present approach works efficiently when the building direction is in slight misalignment with the vertical direction.

building direction

vertical


Input: The columnar to equiaxed transition (CET) of grain structures associated with processing conditions has been observed during metallic additive manufacturing (AM).

transition

grain structures

metallic additive manufacturing

AM


Input: However, the formation mechanisms of these grain structures have not been well understood under rapid solidification conditions, especially for AM of superalloys.

grain structures

rapid solidification

AM

superalloys


Input: This paper aims to uncover the underlying mechanisms that govern the CET of AM metals, using a well-tested multiscale phase-field model where heterogeneous nucleation, grain selection and grain epitaxial growth are considered.

AM metals

model

heterogeneous nucleation

grain

grain

epitaxial


Input: Using In718 as an example, the simulated results show that the CET is critically controlled by the undercooling, involving constitutional supercooling, thermal and curvature undercoolings in the melt pool, which dictates the extent of heterogeneous nucleation with respect to the grain epitaxial growth during rapid solidification.

as

melt pool

supercooling

heterogeneous nucleation

grain

epitaxial

rapid solidification


Input: Laser Additive Manufacturing (LAM) of light metals such as high-strength Al-based alloys offers tremendous potential for e.g.

Laser Additive Manufacturing

LAM

light metals

as

alloys


Input: weight reduction and associated reduced fuel consumptions for the transportation industry.

weight

reduction

industry


Input: Typically, commercial Sc-containing alloys, such as Scalmalloy®, rely on precipitation hardening to increase their strength.

alloys

as

precipitation hardening

strength


Input: Conventional processing involves controlled ageing during which ordered and coherent Al3Sc precipitates form from a Sc-supersaturated solid solution.

precipitates

solid solution


Input: Here we show how the intrinsic heat treatment (IHT) of directed energy deposition (DED) can be used to trigger the precipitation of Al3Sc already during the LAM process.

heat treatment

directed energy deposition

DED

LAM

be

precipitation


Input: High number densities of 1023 nano-precipitates per m3 can be realized through solid-state phase transformation from the supersaturated Al-Sc matrix that results from the fast cooling rate in LAM.

be

solid-state phase

cooling rate

LAM


Input: Yet, the IHT causes precipitates to coarsen, hence reducing their strengthening effect.

precipitates

strengthening


Input: We implement alternative solidification conditions to exploit the IHT to form a Zr-rich shell around the Al3Sc precipitates that prevents coarsening.

solidification

shell

precipitates


Input: Our approach is applicable to a wide range of precipitation-hardened alloys to trigger in-situ precipitation during LAM.

range

alloys

in-situ

LAM


Input: Thermo-mechanical finite element modeling of additive manufacturing processes, such as Directed Energy Deposition and Laser Powder Bed Fusion, has been widely applied for the prediction and mitigation of part distortion.

Thermo-mechanical

finite element

Deposition

prediction

distortion

additive manufacturing processes

Laser Powder Bed Fusion

as


Input: However, as the size of modeled geometries gets larger, the number of nodes and elements required in the finite element mesh increases significantly.

as

elements

geometries

finite element


Input: Because runtime will increase as more nodes are added, it is not practical to conduct full simulations of large builds using standard static meshes.

as

simulations

builds

standard


Input: Advanced meshing strategy is required to reduce the run time and to retain the accuracy of the prediction.

accuracy

prediction


Input: In this work, a mesh coarsening strategy is evaluated for predicting temperature, distortion, and residual stress in additive manufacturing, aiming to achieve feasible run times with reasonable accuracy on large builds.

temperature

distortion

residual stress

additive manufacturing

accuracy

builds


Input: Directed Energy Deposition of thin wall geometries built from Inconel® 625 and Ti6Al4V is used as a reference and models with 2 levels of Octree mesh coarsening are investigated.

Directed Energy Deposition

geometries

as


Input: The thermal history, in situ distortion, residual stress, and run times are compared with previously experimentally validated static mesh results.

in situ

distortion

experimentally validated

residual stress


Input: Two levels of mesh coarsening is found to be the most effective case for both materials reducing the computational time by 75% while reporting less than 2.5% error for the peak distortion and negligible error for the thermal history difference as compared to the static mesh.

be

as

materials

error

distortion

error


Input: Keeping two fine layers of elements underneath the heat source is found to be the most efficient in terms of prediction accuracy and run time.

elements

be

heat source

prediction

accuracy


Input: Cork powder residues were used to produce a biodegradable filament for additive manufacturing.

Cork

filament

additive manufacturing


Input: The addition of a maleic anhydride-based coupling agent to the PLA matrix improved the mechanical behavior of CPC.

PLA

mechanical


Input: A cork-like filament fully biodegradable and filled with low granulometry cork powder residues was developed.

filament

cork


Input: Cork-polymer composites (CPC) were prepared using a Brabender type mixer incorporating 15% (w/w) of cork powder (corresponding to 55% (v/v)) and having polylactic acid (PLA) as matrix.

composites

cork

polylactic acid

PLA

as


Input: In order to promote a chemical adhesion between cork particles and PLA, the effect of maleic anhydride grafted PLA (MAgPLA) was studied.

adhesion

cork

PLA

PLA


Input: Fourier Transform Infrared–Attenuated Total Reflection (FTIR-ATR) analysis was used to evaluate the functionalization of MAgPLA onto the polymeric chain.

Fourier Transform Infrared

Reflection


Input: The addition of MAgPLA enhanced the mechanical behavior by increasing tensile properties while improving the dispersion of cork particles within PLA matrix.

mechanical

tensile properties

dispersion

cork

PLA


Input: In addition, cork particles and MAgPLA acted as nucleating agents during PLA melting process.

cork

as

PLA

melting


Input: To evaluate the printability of the developed CPC filament, specimens were printed by Fused Filament Fabrication (FFF) and compared to those obtained by injection molding (IM).

printability

filament

Fused Filament Fabrication

FFF

injection molding


Input: FFF allowed to preserve the cork alveolar structure in the specimens, benefiting CPC mechanical behavior.

FFF

cork

structure

mechanical


Input: 3D parts could be printed with the CPC filament thereby demonstrating the usefulness of the fully biodegradable cork-based filament here developed.

3D parts

be

filament

filament


Input: 3D printed parts exhibit unique characteristics, such as a nonplastic and warm touch, a natural colour and the release of a pleasant odour during the printing process.

3D printed parts

as

printing process


Input: AISI 316L steel was tested under high Hertzian loads at different temperatures.

steel

temperatures


Input: The 3D printed material presents higher wear resistance.

3D printed

wear resistance


Input: The triboxides present the same chemical composition.

chemical composition


Input: The material produced using SLM presents a thinner strain-hardened layer.

material

SLM

layer


Input: The 3D printed material begins dynamic recrystallization at higher temperatures.

3D printed

dynamic

temperatures


Input: This material is also suitable for use in the 3D printing of metal components.In this study, the wear behavior of AISI 316L steel produced using Selective Laser Melting technology was investigated in order to determine its metallurgical evolution under high Hertzian stress.

material

metal

steel

3D printing

Selective Laser Melting

wear

evolution

metallurgical

stress


Input: The results were compared to AISI 316L that was classically forged.A preliminary mechanical and microstructural characterization was carried out in order to characterize the material and compare the properties of 3D printed with material that has been forged.

mechanical

microstructural characterization

material

material

properties

3D printed


Input: The wear rates were then calculated using a stylus profilometer.

wear

stylus profilometer


Input: The wear tracks were characterized in the top view to determine the composition of the triboxide layer using SEM-EDXS and Raman spectroscopy.

wear

composition

layer

Raman spectroscopy


Input: Cross sections of the samples were then used to conduct SEM analysis in order to determine the thickness of the tribolayer and the characteristics of the strain hardened layer.

Cross sections

samples

SEM

strain

hardened


Input: EBSD mapping was also conducted on the same samples to determine the regions in which recrystallization had taken place.The results showed that the 3D printed material has lower wear rates than the forged material, due to the finer microstructure of the material produced by 3D.

EBSD

samples

recrystallization

wear

3D printed

material

material

finer microstructure


Input: In addition, the triboxides formed on the additively manufactured component were finer, although the nature of the oxide was the same.

additively manufactured

oxide


Input: The 3D printed material showed a dynamic recrystallization at 600 °C, while the forged material started to recrystallize at 200 °C.

3D printed

dynamic

material


Input: Medium powered LPBF machines can process pure Cu to an acceptable level.

LPBF

process

Cu


Input: Resistivity of as-built Cu increases by 33% depending on build orientation.

Resistivity

Cu

build orientation


Input: Resistivity can be reduced by over 50% from as-built conditions via heat treatment.

Resistivity

be

heat treatment


Input: Electrical resistivity values once heat treated are lower than AlSi10Mg values.

Electrical resistivity

heat


Input: Pure copper is an excellent thermal and electrical conductor, however, attempts to process it with additive manufacturing (AM) technologies have seen various levels of success.

copper

conductor

electrical

process

technologies

additive manufacturing

AM


Input: While electron beam melting (EBM) has successfully processed pure copper to high densities, laser powder bed fusion (LPBF) has had difficulties achieving the same results without the use of very high power lasers.

electron beam melting

EBM

laser powder bed fusion

LPBF

processed

copper

power


Input: This requirement has hampered the exploration of using LPBF with pure copper as most machines are equipped with lasers that have low to medium laser power densities.

LPBF

copper

as

machines

laser power


Input: In this work, experiments were conducted to process pure copper with a 200 W LPBF machine with a small laser spot diameter resulting in an above average laser power density in order to maximise density and achieve low electrical resistivity.

process

diameter

average

copper

LPBF

laser

power

density

density

electrical resistivity


Input: The effects of initial build orientation and post heat treatment were also investigated to explore their influence on electrical resistivity.

build orientation

heat treatment

electrical resistivity


Input: It was found that despite issues with high porosity, heat treated specimens had a lower electrical resistivity than other common AM materials such as the aluminium alloy AlSi10Mg.

porosity

heat

electrical resistivity

AM materials

as

aluminium alloy AlSi10Mg


Input: By conducting these tests, it was found that despite having approximately double the resistivity of commercially pure copper, the resistivity was sufficiently low enough to demonstrate the potential to use AM to process copper suitable for electrical applications.

resistivity

resistivity

copper

copper

AM

process

electrical applications


Input: Large Area Additive Manufacturing now enables the fabrication of structures that are dramatically more substantial than those produced with standard 3D printing.

Area

Additive Manufacturing

fabrication

3D printing

standard


Input: As the use of support structure is generally not appropriate when printing at these scales, understanding the limits of overhanging feature angles is necessary to establish the economic case for using large 3D printing.

As

support structure

overhanging feature

limits

3D printing


Input: Additionally, understanding the physics of the process is paramount to avoiding expensive failed prints.

physics

process


Input: Rapid sequential layers can result in slumping as the structure retains excessive heat when the next layer is printed.

as

structure

heat

layer


Input: The model can be used to insert additional dwell times after each layer so that the next layer of printing initiates after the previous layer is sufficiently cool such that the existing structure is appropriately solidified.

model

structure

be

insert

dwell times

layer

layer

layer


Input: Inputs to the model include the feedstock material, the number of beads in the overhanging wall, the angle of overhang and the threshold of failure represented as out-of-plane displacement from the intended geometry.

model

failure

geometry

feedstock material

as

beads

overhang


Input: The proposed thermal model can then be used with slicing software to insert pauses a priori, or can be leveraged during the print in conjunction with infrared imaging in order to provide in situ process control to improve quality and yield.

model

slicing

infrared

in situ

quality

be

be

insert

print

imaging


Input: Selective Laser Melting (SLM) as an additive manufacturing process can fabricate near to net shape metallic components directly from Computer aided design models, which may be difficult to fabricate using conventional manufacturing methods.

Selective Laser Melting

SLM

additive manufacturing process

fabricate

net shape

fabricate

conventional manufacturing

as

metallic

be

components

Computer aided design


Input: In this work, the powdered metals used as the raw material feedstock in the Selective Laser Melting (SLM) process were studied.

powdered metals

as

raw material

feedstock

Selective Laser Melting

SLM

process


Input: SLM manufacturing processibility of nickel based super alloy, powders related to the particle Size Distribution (PSD), flow ability, mechanical properties and microstructures was investigated.

SLM manufacturing

nickel

super alloy

powders

microstructures

particle Size Distribution

mechanical properties


Input: Different powder characterisation methods were also investigated to establish which might be most useful for SLM application.

powder

be

SLM


Input: Three different Inconel 625 (IN625) powder feedstock materials have been accounted for this study.

Inconel 625

powder feedstock

materials


Input: Firstly, three different IN625 powders were fully characterised for chemical composition, particle size distribution and flow ability using different types of characterisation techniques.

powders

chemical composition

particle size distribution


Input: It has been found that the presence of any significant proportion of powder particles smaller than 10-μm diameter, leads to severe agglomeration and make SLM processing difficult.

powder particles

diameter

SLM


Input: Secondly, coupons were manufactured using SLM from each powder with different process parameter, which were analysed for porosity and mechanical behaviour.

manufactured

process parameter

mechanical behaviour

SLM

powder

porosity


Input: Next, the scanning electron microscopy (SEM), electron back scattering diffraction (EBSD) are employed to investigate the microstructures.

scanning electron microscopy

SEM

diffraction

EBSD

microstructures


Input: Finally, data analysis was employed on the data collected by metal powders characterization, SLM manufacturing, SEM/EBSD study and mechanical properties of the IN625.

data

data

mechanical properties

metal powders

SLM manufacturing


Input: It has been observed that the powder characteristics, as well as SLM process parameters influences on the quality of the IN625 fabricated.

powder

as

as

process parameters

quality

fabricated


Input: Binder jetting additive manufacturing (BJAM) is a comparatively low-cost process that enables manufacturing of complex and customizable metal parts.

Binder jetting additive manufacturing

manufacturing

process

metal


Input: This process is applied to low-cost water-atomized iron powder with the goal of understanding the effects of printing parameters and sintering schedule on maximizing the green and sintered densities of manufactured samples, respectively.

process

parameters

manufactured

iron

sintering

sintered


Input: The powder is characterized by using scanning electron microscopy (SEM) and particle size analysis (Camsizer X2).

powder

scanning electron microscopy

SEM

particle


Input: In the AM process, the effects of powder compaction, layer thickness, and liquid binder level on green part density are investigated.

AM process

compaction

powder

liquid binder

layer thickness

green part

density


Input: Post-process heat treatment is applied to selected samples, and suitable debinding parameters are studied by using thermo-gravimetric analysis (TGA).

Post-process heat

samples

debinding

TGA


Input: Sintering at various temperatures and durations results in densities of up to 91.3%.

Sintering

temperatures


Input: Image processing of x-ray computed tomography (μCT) scans of the samples reveals that porosity distribution is affected by powder spreading, and gradients in pore distribution in the sample are largely reduced after sintering.

Image

samples

distribution

distribution

sample

x-ray computed tomography

porosity

pore

powder

sintering


Input: The results indicate that the sintering temperature and time might be tailored to achieve target densities anywhere in the range of 64% and 91%, with possibly higher densities by increasing sintering time.

sintering

be

range

sintering time


Input: Binder-jetting, an additive manufacturing process and relatively low-cost technology is utilized to deposit complex-shaped thin ceramic cores.

additive manufacturing process

low-cost technology

complex-shaped

ceramic cores


Input: In this study, for enhancing sintering quality, a decomposable binder was prepared using binder-jetting by dispersing different contents of zirconium basic carbonate (ZBC) into an inorganic colloidal binder.

sintering

quality

binder

zirconium

colloidal binder


Input: The effects of different ZBC contents on the printability of the binder and the performance characteristics of the ceramic cores by binder-jetting were investigated.

printability

binder

performance

ceramic cores


Input: The results show that the surface tension of the binder decreases with the increasing of ZBC contents, indicating that the addition of ZBC particles perturbs the interaction between water molecules.

surface tension

binder

particles


Input: The presence of newly generated ZrO2 particles decomposed by ZBC demonstrated a significant effect on the mechanical properties of the ceramic cores.

particles

mechanical properties

ceramic cores


Input: The sintered density increased by about 44%, the bending strength improved from 60 to 79 MPa, and linear shrinkage decreased from 20 to 13% after sintering at 1500 °C as the ZBC content was increased from 0 to 35 wt%.

sintered

sintering

density

bending strength

MPa

shrinkage

as


Input: Purposely introduced gas pores in wire + arc additive manufactured titanium (WAAM Ti-6Al-4 V).

gas

wire + arc additive manufactured

WAAM

titanium

Ti-6Al-4 V


Input: Interrupted fatigue testing with X-ray computed tomography scanning at intervals.

fatigue testing

X-ray computed tomography

scanning


Input: Changes in porosity morphology observed with fatigue loading cycles.

porosity

fatigue

morphology


Input: Cyclic stress-strain response in the vicinity of gas pores calculated by finite element method.

gas

finite element method


Input: Fatigue life predicted using the traditional notch fatigue approach.

Fatigue life

fatigue

notch


Input: Porosity defects remain a challenge to the structural integrity of additive manufactured materials, particularly for parts under fatigue loading applications.

Porosity

structural integrity

fatigue

defects

additive manufactured


Input: Although the wire + arc additive manufactured Ti-6Al-4 V builds are typically fully dense, occurrences of isolated pores may not be completely avoided due to feedstock contamination.

wire + arc additive manufactured

Ti-6Al-4 V

be

feedstock

builds

fully dense

pores


Input: This study used contaminated wires to build the gauge section of fatigue specimens to purposely introduce spherical gas pores in the size range of 120–250 micrometres.

build

range

gauge section

fatigue

spherical gas pores


Input: Changes in the defect morphology were monitored via interrupted fatigue testing with periodic X-ray computed tomography (CT) scanning.

defect

scanning

fatigue testing

X-ray computed tomography

CT


Input: Prior to specimen failure, the near surface pores grew by approximately a factor of 2 and tortuous fatigue cracks were initiated and propagated towards the nearest free surface.

failure

surface

free surface

pores

fatigue


Input: Elastic-plastic finite element analysis showed cyclic plastic deformation at the pore root as a result of stress concentration; consequently for an applied tension-tension cyclic stress (stress ratio 0.1), the local stress at the pore root became a tension-compression nature (local stress ratio −1.0).

finite element analysis

plastic deformation

pore

cyclic stress

stress

stress

pore

stress

as

stress concentration


Input: Fatigue life was predicted using the notch fatigue approach and validated with experimental test results.

Fatigue life

fatigue

predicted

experimental

notch


Input: Processing-structure-property relationships in material extrusion additive manufacturing are complex, non-linear, and poorly understood.

material extrusion additive manufacturing


Input: In this work, we designed an informatics workflow for the collection of high pedigree data from each stage of the fused filament fabrication (FFF) printing process.

designed

workflow

data

fused filament fabrication

FFF

printing process


Input: In conjunction with a design of experiments, we applied the workflow to investigate the influences of processing parameters on weld strength across three commercially available FFF printers.

design of experiments

workflow

parameters

weld strength

FFF


Input: Environmental, material, and print conditions that may impact performance were monitored to ensure that relevant data were collected in a consistent manner.

material

print

impact

data


Input: Acrylonitrile butadiene styrene (ABS) filament was used to print ASTM D638-14 Type V tensile bars.

Acrylonitrile butadiene styrene

ABS

filament

V

print

tensile bars


Input: Data were analyzed using multivariate statistical techniques, including principal component analysis.

Data

multivariate

component


Input: The magnitude of the effects of extrusion temperature, layer thickness, print bed temperature, and print speed on the tensile properties of the final print were determined.

magnitude

layer thickness

extrusion

print

print

print

bed

tensile properties


Input: The results demonstrated that printer selection is important and changes the impact of print parameters.

printer

impact

parameters

print


Input: Non-destructive dielectric imaging during additive manufacturing.

dielectric

additive manufacturing


Input: 3D characterization of relative dielectric permittivity within printed devices.

dielectric


Input: Integrated, in-line quality control technique for AM processes.

quality control

AM processes


Input: Additive manufacturing (AM) techniques are used increasingly for the direct fabrication of microwave devices, such as graded index lenses and dielectric resonator antennas, which have spatially-varying dielectric properties (i.e.

Additive manufacturing

AM

fabrication

microwave

as

dielectric

dielectric


Input: However, there is no effective method to characterize the spatial distribution of permittivity within the printed component, either during manufacture or once the component is complete.

spatial distribution

component

component

manufacture


Input: Therefore it is not possible to confirm the extent to which the manufactured spatial distribution of permittivity meets the intended design.

manufactured

distribution

design


Input: We report the integration of a novel split ring resonator (SRR) surface mapping technique directly into an AM process to make non-destructive in-line measurements of the local relative dielectric permittivity (ϵr) within 3D objects as they are formed.

resonator

3D objects

surface

AM process

dielectric


Input: We then reconstruct these data into 3D dielectric “images” of the printed component.

data

images

component


Input: Detailed insights into the dielectric imaging principle, data processing/analysis, as well as limitations and opportunities related to the technique are described.

dielectric

data

as

as


Input: The work aims to accelerate the design-make-test cycle for advanced microwave devices, and suggests the possibility for real-time, closed-loop control of dielectric properties during AM.

microwave

closed-loop control

dielectric

AM


Input: Variation of texture in Ti-6Al-4V samples produced by three different additive manufacturing (AM) processes has been studied by neutron time-of-flight (TOF) diffraction.

Variation

samples

processes

neutron

texture

additive manufacturing

AM

diffraction


Input: The investigated AM processes were electron beam melting (EBM), selective laser melting (SLM) and laser metal wire deposition (LMwD).

AM processes

electron beam melting

EBM

selective laser melting

SLM

laser

deposition


Input: Additionally, for the LMwD material separate measurements were done on samples from the top and bottom pieces in order to detect potential texture variations between areas close to and distant from the supporting substrate in the manufacturing process.

material

substrate

samples

texture

areas

manufacturing process


Input: Electron backscattered diffraction (EBSD) was also performed on material parallel and perpendicular to the build direction to characterize the microstructure.

diffraction

EBSD

material

build direction

microstructure


Input: Understanding the context of texture for AM processes is of significant relevance as texture can be linked to anisotropic mechanical behavior.

texture

AM processes

as

be

anisotropic


Input: It was found that LMwD had the strongest texture while the two powder bed fusion (PBF) processes EBM and SLM displayed comparatively weaker texture.

texture

texture

powder bed fusion

PBF

EBM

SLM

processes


Input: The texture of EBM and SLM was of the same order of magnitude.

texture

EBM

SLM

magnitude


Input: These results correlate well with previous microstructural studies.

microstructural


Input: Additionally, texture variations were found in the LMwD sample, where the part closest to the substrate featured stronger texture than the corresponding top part.

texture

texture

sample

substrate


Input: The crystal direction of the α phase with the strongest texture component was [112¯3].

phase

texture

component


Input: Carries out in situ high speed imaging of polymer extrusion additive manufacturing.

in situ

imaging

polymer extrusion additive manufacturing


Input: Measures thermal conductivity of built part as a function of process parameters.

thermal conductivity

as

process parameters


Input: Develops correlation between process, microstructure and thermal properties.

process

microstructure

thermal properties


Input: Results show strong dependence of thermal property on raster speed & layer height.

thermal property

layer height


Input: Results may be helpful for process optimization to obtain novel, functional parts.

be

process optimization


Input: Additive manufacturing has gained significant research attention due to multiple advantages over traditional manufacturing technologies.

Additive manufacturing

traditional manufacturing

research

technologies


Input: A fundamental understanding of the relationships between process parameters, microstructure and functional properties of built parts is critical for optimizing the additive manufacturing process and building parts with desired properties.

process parameters

microstructure

properties

properties

additive manufacturing process


Input: This is also critical for a multi-functional part where the process needs to be optimized with respect to disparate performance requirements such as mechanical strength and thermal conductivity.

process

performance

be

as

strength

thermal conductivity


Input: This paper presents in situ high speed imaging and build-direction thermal conductivity measurements of polymer extrusion based additively manufactured parts in order to understand the effect of process parameters such as raster speed, infill percentage and layer height on build-direction thermal conductivity.

in situ

process parameters

imaging

thermal conductivity

thermal conductivity

polymer extrusion

additively manufactured

as

infill percentage

layer height


Input: Measurements of thermal conductivity using a one-dimensional heat flux method are correlated with in situ process images obtained from a high speed camera as well as cross section images of the built part.

thermal conductivity

heat flux

correlated

in situ

images

images

camera

as

as


Input: Results indicate strong dependence of build-direction thermal conductivity on raster speed, layer thickness and infill percentage, which is corroborated by high speed imaging of the printing process at different values of these process parameters.

thermal conductivity

layer thickness

infill percentage

imaging

printing process

process parameters


Input: Key trade-offs between process throughput and thermal properties are also identified.

process

thermal properties


Input: In addition to enhancing our fundamental understanding of polymer extrusion based additive manufacturing and its influence on thermal properties of built parts, results presented here may facilitate process optimization towards parts with desired thermal and multi-functional properties.

polymer extrusion

additive manufacturing

thermal properties

process optimization

properties


Input: Lightweight design is an area of mechanical engineering that becomes increasingly important in many industries, as they pursue reduced mass and more efficient parts.

Lightweight

design

area

mechanical engineering

industries

as


Input: A special class of materials for load-bearing structures are metallic cellular materials with cubic unit cells, which can be manufactured conveniently through laser beam melting (LBM).

materials

unit cells

laser beam

load-bearing

metallic

cellular materials

be


Input: Such materials exhibit a rather complex microstructure and can be analysed using analytical and numerical methods wherein the determination of properties such as relative density, effective elastic and yield strength properties is of special interest.

materials

microstructure

properties

be

as

density

elastic and yield strength


Input: This paper addresses closed-form analytical methods based on beam theories for the determination of the effective properties of additively manufactured microstructures such as lattices, and a comparison with experimental results [1], [2] which leads to excellent agreements for relative densities lower than 40%, although results reveal a great dependency on the manufacturing strategy.

beam

properties

experimental

additively manufactured

manufacturing

as

relative densities


Input: Lastly, a classification concerning the topology of the cellular units is presented as well in order to help the engineer choose appropriate geometries for specific application purposes.

classification

topology

geometries

as


Input: In conclusion, this structural concept may be applied in many fields such as bioengineering and in functional graded materials as they are applied in lightweight engineering.

be

as

functional graded materials

as

lightweight

engineering


Input: Polymeric Pellet-Based Additive Manufacturing (PPBAM) systems are increasing in the field of 3D printing as a result of the evolution of additive technologies as their development process consolidates and expands.

Additive Manufacturing

3D printing

evolution

process

additive technologies


Input: New opportunities for industrial integration of additive manufacturing (AM) technologies are identified, including AM of large polymeric parts.

industrial

additive manufacturing

AM

AM

technologies


Input: The PPBAM process consists of adapting a pellet-fed extrusion mechanism to a displacement system, either a Cartesian mechanism or a robotic arm system, building parts in a multi-layered approach.

process

mechanism

extrusion

robotic arm


Input: This use is justified by the extruded filament sizes required and the material costs when facing large-format prints.

extruded

facing

material


Input: In this article, a pellet extrusion based printer prototype is presented together with a case study.

pellet

case study

extrusion

printer


Input: The case study consists of the development of a two cubic meter capacity plastic part for the naval industry with a topology optimization design approach and material selection and validation methodology for a large-volume pellet based extrusion system.

case study

capacity

validation methodology

pellet

meter

industry

topology optimization

design

material

extrusion


Input: Two functional prototypes were developed with the selected materials from the explained methodology a PLA and a flame retardant ABS, and post processed to full fill the actual product´s specifications.

functional prototypes

materials

methodology

processed

PLA

flame retardant

ABS

specifications


Input: The first report on the fatigue behavior of additively manfacutred (AM) biodegradable porous Mg alloy (WE43) and how it is affected by biodegradation.

fatigue

porous

AM

Mg alloy


Input: Biodegradation decreased the fatigue strength of the porous material from 30% to 20% of its yield strength.

fatigue strength

yield strength

porous material


Input: Moreover, cyclic loading significantly increased its biodegradation rate.

cyclic loading


Input: The mechanistic aspects of how biodegradation and cyclic loading interacted with each other on both micro and macro scales were revealed.

cyclic loading

macro scales


Input: Additively manufactured (AM) biodegradable metals with topologically ordered porous structures hold unprecedented promise as potential bone substitutes.

Additively manufactured

AM

biodegradable metals

as

topologically

porous

bone


Input: There is, however, no information available in the literature regarding their mechanical performance under cyclic loading or the interactions between biodegradation and cyclic loading.

mechanical

cyclic loading

cyclic loading


Input: We therefore used selective laser melting (SLM) to fabricate porous magnesium alloy (WE43) scaffolds based on diamond unit cells.

selective laser melting

SLM

fabricate

magnesium alloy

diamond

scaffolds

cells


Input: The microstructure of the resulting material was examined using electron back-scattered diffraction, scanning transmission electron microscopy, and X-ray diffraction.

microstructure

material

diffraction

scanning transmission electron microscopy

X-ray diffraction


Input: The fatigue behaviors of the material in air and in revised simulated body fluid (r-SBF) were evaluated and compared.

fatigue

material

fluid


Input: Biodegradation decreased the fatigue strength of the porous material from 30% to 20% of its yield strength.

fatigue strength

yield strength

porous material


Input: Moreover, cyclic loading significantly increased its biodegradation rate.

cyclic loading


Input: The mechanistic aspects of how biodegradation and cyclic loading interacted with each other on different scales were revealed as well.

cyclic loading

as


Input: In addition, dislocations became more tangled after the fatigue tests.

dislocations

fatigue tests


Input: On the macro-scale, cracks preferred initiating at the strut junctions where tensile stress concentrations were present, as revealed by the finite element analysis of the porous material under compressive loading.

strut

junctions

tensile stress

compressive loading

as

porous material

finite element analysis


Input: Further improvements in the biodegradation-affected fatigue performance of the AM porous Mg alloy may therefore be realized by optimizing both the topological design of the porous structure and the laser-processing parameters that determine the microstructure of the SLM porous material.

fatigue

porous

AM

SLM

Mg alloy

be

porous material

topological design

parameters

microstructure


Input: Additive manufacturing workflow was employed for fabrication of patient-specific fracture fixation implants.

Additive manufacturing

fabrication

fracture

implants


Input: Orthotropic material properties of AM implants along with their biomechanical behavior were investigated using experimental and computational methods.

Orthotropic

material properties

experimental

AM

biomechanical

computational methods


Input: medial fracture gap displacement) by 47.2% and risk of screw cut-out by 14.6% when compared to the conventional plate design.

fracture

screw

design


Input: Recent advancements in additive manufacturing (AM) have motivated researchers to consider this fabrication technique as a solution for challenges in patient-specific orthopaedic needs.

additive manufacturing

AM

fabrication

as

solution

orthopaedic


Input: Although there is an increasing trend in the applications of AM in medical fields, there is a critical need to understand the biomechanical performance of AM implants.

trend

AM

AM

medical

biomechanical


Input: In particular, design opportunities, anisotropic material properties and resulting stability of AM implant constructs for large bone defects such as osteosarcoma, comminuted fractures and infections are unexplored.

design

anisotropic material properties

stability

AM

bone defects

as


Input: This study aims to evaluate metal AM for complex fracture fixation using both computational and experimental methods.

metal AM

fracture

experimental


Input: In addition, this research highlights the role of AM in the entire workflow to fabricate metal AM fixation plates for treatment of comminuted proximal humerus fractures.

research

workflow

AM

fabricate

AM


Input: A new AM-centric patient-specific implant design for reducing common postoperative complications such as varus collapse and screw cutout is investigated.

implant

design

as

screw


Input: Biocompatible 316L stainless steel specimens processed in laser-powder bed fusion (L-PBF) is subjected to tensile testing and post-hoc microhardness to obtain orthotropic material properties of the AM implants.

Biocompatible

316L stainless steel

orthotropic

processed

microhardness

material properties

bed fusion

L-PBF

AM

tensile testing


Input: Subsequently, risk of screw cut-out is evaluated using finite element modelling (FEM) of AM implant-bone constructs.

screw

finite element modelling

FEM

AM


Input: medial fracture gap displacement) by 47.2% and risk of screw cut-out by 14.6% when compared to the conventional plate design.

fracture

screw

design


Input: Findings from this study can be extended to other patient anatomy, loading conditions, and AM processes.

be

AM processes


Input: The feasibility of a hybrid additive manufacturing (AM) method combining material extrusion and powder bed binder jetting (PBBJ) techniques for fabrication of structures made of silicone (polysiloxane) is investigated in this paper.

feasibility

additive manufacturing

AM

material extrusion

powder bed binder jetting

fabrication

silicone


Input: A full factorial experimental design was conducted to maximize the geometrical accuracy of the parts.

experimental design

accuracy


Input: The rheological and morphological properties of the silicone powders, the thermal characteristics of the liquid silicone binder, and mechanical characterization the additively manufactured parts are reported.

rheological

properties

silicone powders

silicone binder

mechanical

additively manufactured


Input: Using this hybrid AM method, porous cylindrical structures (5 mm diameter (D) × 3 mm height (H)) with potential applications in biomedical industry were additively manufactured.

AM

mm

mm

additively manufactured

porous

cylindrical

diameter

biomedical industry


Input: The final structures are composed of ∼60% silicone powder, ∼ 30% silicone binder, and < 10% air voids.

silicone powder

silicone binder

voids


Input: These three phases are distributed throughout the structure in a non-uniform fashion.

structure

fashion


Input: Powder bed binder jetting additive manufacturing was used for the first time to produce porous silicone (polysiloxane) structures.Download: Download high-res image (285 Additive manufacturing of soft magnetic materials and components based on laser powder bed fusion (L-PBF) offers new opportunities for soft magnetic core materials in efficient energy converters.

Powder bed binder jetting additive manufacturing

Additive manufacturing

laser powder bed fusion

L-PBF

porous

high-res image

materials

components

core


Input: For more favorable material compositions like FeSi6.7 (strategy 1) with larger electrical resistivity and close-to-zero magnetostriction a maximum permeability of μmax = 31,000, minimum coercivity of Hc = 16 A/m and hysteresis losses of 0.7 W/kg at 1 T and 50 Hz have been realized.

material

electrical resistivity

magnetostriction

permeability

hysteresis


Input: Feasibility, functionality and potential of the different strategies (and combinations thereof) are discussed based on first prototypes and supporting simulations.

Feasibility

prototypes

simulations


Input: The results are compared to conventional electrical steel and SMC (soft magnetic composites).

electrical

composites


Input: This work investigates the feasibility of a binderless, extrusion-based additive manufacturing approach to fabricate alumina (Al2O3) parts from nanopowder.

investigates

feasibility

additive manufacturing

fabricate

alumina


Input: Traditional manufacture of ceramics with subtractive methods is limited due to their inherent hardness and brittleness, inevitably leading to ceramic parts with less-than-optimal geometries for the specific application.

manufacture

geometries

ceramics

ceramic

subtractive

hardness


Input: With an additive manufacturing approach, ceramic parts with complex 3D geometries, including overhangs or hollow enclosures, become possible.

additive manufacturing

ceramic

3D geometries

overhangs


Input: These complex ceramic parts are highly valuable in heat exchanger, condenser, biomedical implant, chemical reactant vessel, and electrical isolation applications.

ceramic

heat exchanger

biomedical

electrical


Input: This research employed direct coagulation of alumina nanopowder slurries with the polyvalent salt tri-ammonium citrate providing the solidification mechanism in an extrusion-based printing process.

research

coagulation

solidification mechanism

alumina

salt

printing process


Input: The viscosity of the slurries was adjusted from ∼35 Pa-s to ∼1000 Pa-s by adjusting pH from ∼9 to ∼4, resulting in a paste that is suitable for extrusion, which retains near-net geometry.

viscosity

pH

geometry

extrusion


Input: It was shown that the direct coagulation approach can be used to create a suspension with tuneable flow characteristics and coagulation rate, and a mechanism describing the process was proposed.

coagulation

coagulation

mechanism

process

be


Input: The direct coagulation printing (DCP) method is described in detail, including how slurry is extruded, solidified, and printed in complex geometries, and sintered to full density.

coagulation

complex geometries

slurry

extruded

sintered

density


Input: Parts were printed with a sintered resolution of 450 μm and green densities as high as 65%.

sintered

resolution

as

as


Input: Mechanical properties were characterized with a comparison to different materials and methods from literature, showing hardness and flexural modulus up to ∼1800 HV and 400 GPa, respectively.

Mechanical properties

materials

hardness

GPa


Input: Heat transfer in standoff region between nozzle tip and bed is critical.

Heat transfer

standoff

nozzle

bed


Input: Carries out infrared based temperature measurement in standoff region.

infrared

temperature

measurement

standoff


Input: Develops analytical model to predict temperature distribution in standoff region.

model

distribution

temperature

standoff


Input: Shows good agreement between measurements and model in wide range of parameters.

model

parameters

range


Input: Contributes towards accurate thermal design of polymer additive manufacturing.

accurate

design

polymer additive manufacturing


Input: Dispensing of a polymer filament above its glass transition temperature is a critical step in several polymer-based additive manufacturing techniques.

polymer filament

glass transition temperature

step

additive manufacturing


Input: While the nozzle assembly heats up the filament prior to dispense, it is important to minimize cooling down of the filament in the standoff distance between the nozzle tip and bed.

nozzle

standoff

nozzle

bed

assembly

cooling

filament

filament


Input: While heat transfer processes within the nozzle assembly, such as filament melting, and on the bed, such as thermally-driven filament-to-filament adhesion, have been well studied, there is a lack of work on heat transfer in the filament in the standoff region.

heat transfer

heat transfer

nozzle

bed

standoff

assembly

melting

as

as

filament

adhesion


Input: This paper presents infrared thermography based measurement of temperature distribution in the filament in the standoff region, and an analytical model for heat transfer in this region.

infrared

distribution

model

heat transfer

measurement

temperature

filament

standoff


Input: The analytical model, based on a balance between thermal advection and convective/radiative heat loss predicts an exponentially decaying temperature distribution, the nature of which is governed by the characteristic length, a parameter that combines multiple process parameters such as mass flowrate, filament diameter, heat capacity and cooling conditions.

model

heat

distribution

parameter

process parameters

heat capacity

temperature

filament diameter

as

cooling


Input: Experimental data in a wide range of process parameters are found to be in very good agreement with the analytical model.

Experimental data

process parameters

model

range

be


Input: The thermal design space for ensuring minimal temperature drop in the standoff region is explored based on the analytical model.

design space

model

temperature

standoff


Input: Experimental data and theoretical modeling presented here improve our fundamental understanding of heat transfer in polymer additive manufacturing, and may contribute towards design tools for thermal optimization of these processes.

Experimental data

theoretical

heat transfer

optimization

processes

modeling

polymer additive manufacturing

design


Input: A complete understanding of processing-structure-property-performance relationship of additively manufactured (AM) components are critical from an application standpoint.

additively manufactured

AM

components


Input: Therefore, in the current investigation, a comprehensive microstructural characterization and mechanical properties (tensile, fatigue and impact toughness) evaluation of nickel alloy 718 AM by the laser powder bed fusion (L-PBF) technique have been performed.

microstructural characterization

mechanical properties

impact

tensile

fatigue

nickel alloy

AM

laser powder bed fusion

L-PBF


Input: AM builds were made from powders manufactured via different atomization conditions.

AM

atomization

powders

manufactured


Input: Although the standard post-heat treatment procedure led to the removal of severe interdendritic segregation both grain boundary and intra-grain precipitation of δ phase occurred.

standard

segregation

grain boundary

precipitation

phase

led


Input: Regardless of δ phase presence, axial fatigue properties of both the AM builds were similar to design handbook wrought fatigue data.

phase

wrought

data

fatigue

fatigue

AM

design


Input: However, due to the δ phase, impact toughness properties were comparable to the wrought material conditions that exhibited δ phase.

phase

impact

properties

phase

wrought material


Input: Fractured surfaces of Charpy impact samples exhibited crack propagation extensively along the boundaries decorated by δ precipitates.

surfaces

impact

crack propagation

boundaries

precipitates


Input: Variability in the mechanical properties of additively manufactured metal parts is a key concern for their application in service.

Variability

mechanical properties

additively manufactured


Input: One of the parameters affecting the above-mentioned property is solidification texture which is driven by scan patterns and other process variables.

parameters

property

solidification

process

scan patterns


Input: Understanding of how these textures arise in the AM process can provide a pathway to control these features which ultimately decide the final structural material properties.

AM process

material properties


Input: In this work, a Cellular Automata (CA) based two-dimensional microstructure model is formulated and implemented to understand grain evolution in AM.

CA

two-dimensional microstructure

model

grain evolution

AM


Input: Grain evolution in multilayer depositions using various scan patterns in Directed Energy Deposition (DED), Metal Laser Sintering/Selective Laser Melting (MLS/SLM), and Electron Beam Melting (EBM) is presented and qualitatively compared with reported literature.

Grain evolution

scan patterns

Directed Energy Deposition

DED

Electron Beam Melting

EBM

Metal

Laser

Laser


Input: Results show strong correlation of scan patterns with evolving grain orientations.

scan patterns

grain


Input: Variability in grain size and orientation evolution during SLM and EBM processing of metallic materials showed direct influence by exposure to different cooling rates and thermal gradients.

Variability

orientation evolution

exposure

grain size

SLM

EBM

metallic materials

cooling rates

thermal gradients


Input: The similarities between the simulated and reported results lead us to conclude CA based modeling for predicting grain orientation and size in metal AM processes is useful for prediction of continuum level structural properties at global and local length scales.

lead

CA

modeling

grain

prediction

continuum

properties

metal AM

length scales


Input: This paper presents the methodology and findings of a novel piece of research with the purpose of understanding and mitigating distortion caused by the combined processes of additive manufacturing (AM) and post machining to final specifications.

methodology

research

distortion

processes

additive manufacturing

AM

machining

specifications


Input: The research work started with the AM building of a stainless steel 316 L industrial impeller that was then machined by removing around 0.5 mm from certain surfaces of the impeller’ s blades and hub.

research

surfaces

AM

machined

mm

stainless steel

s

industrial


Input: Distortion and residual stresses were experimentally measured.The manufacture of the impeller by AM and then machining was numerically simulated by applying the finite element (FE) method.

Distortion

manufacture

finite element

residual stresses

AM

machining

FE


Input: Distortion and residual stresses were simulated and validated.

Distortion

residual stresses


Input: The FE distortion was then used in a numerical procedure to reverse distortion directions in order to produce a new impeller with mitigated distortion.

FE

distortion

distortion

distortion


Input: A 2-stage hybrid manufacturing supply chain based on metal Additive Manufacturing (AM) is proposed which includes AM hubs, Heat Treatment (HT) facilities and machine shops.

hybrid manufacturing

metal Additive Manufacturing

AM

AM

Heat Treatment

machine


Input: p-median models are applied to identify the optimal location for metal AM hubs in the U.S. that would serve as near-net manufacturers to supply processed build plates to HT facilities who will ship it to machine shops after HT.

metal AM

as

processed

build plates

machine


Input: Fewer number of heat treatment facilities require concentrated locations and fewer AM hubs.

heat treatment

AM


Input: Hybrid Manufacturing is defined as the integration of Additive Manufacturing (AM), specifically metal AM, with traditional manufacturing post-processing such as heat treatment and machining.

Hybrid Manufacturing

post-processing

as

as

Additive Manufacturing

AM

metal AM

traditional manufacturing

machining


Input: Hybrid AM enables Small and Medium Enterprises (SME) who can offer post-processing services to integrate into the growing AM supply chain.

AM

AM

post-processing


Input: Most near-net metal AM parts require heat treatment processes (e.g.

metal AM

heat treatment


Input: residual stress relieving/annealing) before machining to achieve final engineering specification.

residual stress

machining

engineering


Input: This research investigates a two-stage facility model to optimize the locations and capacities for new metal AM hubs which require two sequential post-processing services: heat treatment and machining.

research investigates

model

post-processing

metal AM

heat treatment

machining


Input: Using North American Industry Classification System (NAICS) data for machine shops and heat treatment facilities in the U.S., a p-median location model is used to determine the optimal locations for AM hub centers based on: (1) geographical data, (2) demand and (3) fixed and operational costs of hybrid-AM processing.

Industry

Classification

data

model

data

machine

heat treatment

AM


Input: Results from this study have identified: (a) candidate US counties to locate metal AM hubs, (b) total cost (fixed, operational and transportation), (c) capacity utilization of the AM hubs and (d) demand assignments across machine shops–heat treatment facilities–AM hubs.

metal AM

AM

heat treatment

AM

b

c

capacity

machine


Input: It was found that 2-stage p-Median model identified 22 A M hub locations as the initial sites for AM hubs which grows to 35 A M hubs as demand increases.

model

as

as

AM


Input: It was also found that relatively fewer number of heat treatment facilities than machine shops resulted in a more concentrated locations of AM hubs.

heat treatment

AM

machine


Input: In addition, transportation costs were not adversely affected by the inclusion of as-build plates and showed that including heat treatment facilities as part of the hybrid AM supply chain will be mutually beneficial to all stakeholders of metal hybrid AM supply chain, i.e.

inclusion

as

be

metal

heat treatment

AM

AM


Input: AM → Heat treatment → Machining.

AM

Heat treatment

Machining


Input: Wire arc additive manufacturing (WAAM) is a promising direct energy deposition technology to produce high-value material components with a low buy-to-fly ratio.

Wire arc additive manufacturing

WAAM

direct energy deposition

material

components


Input: WAAM is able to produce thin-walled structures of large scale and also truss structures without any support.

WAAM

truss

support


Input: To manufacture complex parts, process reliability and repeatability are still a necessity and this often leads to long developing times.

manufacture

process

repeatability


Input: In this paper, a method is proposed to automatically manufacture complex truss structures with point by point arc additive manufacturing and a six axis robot.

manufacture

truss

robot

arc additive manufacturing


Input: Computer aided manufacturing (CAM) software is designed to manage (i) material deposition at intersections and (ii) collisions between the part under construction and the torch.

Computer aided manufacturing

CAM

software

deposition

designed

material

construction


Input: Because it is difficult to model the deposition process, the bead geometry is monitored using video imaging.

model

deposition process

bead geometry

imaging


Input: Image treatment program detects the contour of the deposit and computes its current position.

Image

contour


Input: With this position, the CAM software corrects the geometry of the part for future deposition.

CAM

geometry

deposition


Input: Simple case studies are tested to validate the algorithm.

Simple

case studies

algorithm


Input: Two solid free form geometries designed by topology optimization are manufactured with this skeleton arc additive manufacturing process.

geometries

manufactured

designed

topology optimization

arc additive manufacturing


Input: Ti-6Al-4V powders from six different vendors were compared with respect to their microstructures, size-distributions, chemistries, surface appearances, flow behavior, and packing densities.

Ti-6Al-4V powders

microstructures

surface


Input: The analysis approaches followed closely ASTM F3049, the standard guide for characterization of additive manufacturing metal powders.

standard

additive manufacturing

powders


Input: Chemistries, including impurity content, agreed well with the standard requirements.

impurity

standard


Input: Powder particle microstructures revealed acicular alpha prime for all vendors.

Powder particle

microstructures


Input: Quantificational analysis of porosity in the WAAM 2319 alloy was revealed by XCT.

porosity

WAAM

alloy


Input: The formation and evolution of micropores are affected by microstructures.

evolution

microstructures


Input: Evolution mechanisms include particles dissolution, H pore precipitation and growth.

Evolution

particles

pore


Input: Majority of the micropores were adjacent to second phase particles.

second phase particles


Input: Given its detrimental influence on mechanical properties, porosity defect is a major problem for wire + arc additively manufactured (WAAM) Al components.

mechanical properties

defect

porosity

wire + arc additively manufactured

WAAM

Al


Input: We performed X-ray computed tomography, optical microscopy, and scanning electron microscopy to observe the spatial distribution, size, and shape of micropores and reveal their formation and evolution mechanisms during the deposition and heat treatment of the WAAM 2319 Al alloys.

X-ray computed tomography

optical microscopy

scanning electron microscopy

spatial distribution

evolution

deposition

heat treatment

WAAM

Al alloys


Input: Key findings demonstrated that thehydrogenmicropores and solidification microvoids existed in as-deposited alloys.

solidification

alloys


Input: The amounts and morphologies of hydrogen micropores and solidification microvoids varied from the top, middle, and bottom of the wall sample because of the distinct microstructure and second-phase distribution in each section.

morphologies

solidification

sample

microstructure

distribution


Input: After the heat treatment, a significant variation in micropores involving three main evolution mechanisms, namely, hydrogen micropore precipitation, phase particle dissolution, and micropore growth, was observed.

heat treatment

variation

evolution

precipitation

phase particle


Input: Results of this research may provide a solid foundation for the safe application of WAAM Al alloy structures.

research

WAAM

Al alloy


Input: In this study, the heterogeneous anisotropic microstructure and mechanical properties of additively manufactured (CoCrFeMnNi) 99C1 high-entropy alloy (HEA) are comprehensively investigated using experimental and theoretical analyses.

heterogeneous

mechanical properties

experimental

theoretical

anisotropic

additively manufactured

alloy


Input: For the present alloys, the selective laser melting (SLM) process produced orthogonally anisotropic microstructure with not only strong macroscopic morphological but also sharp microscopic crystallographic textures.

alloys

selective laser melting

SLM

process

macroscopic

anisotropic


Input: Moreover, due to the complex thermal gradient and history in the melt pools, the columnar grains were heterogeneously evolved along the building direction with alternatively arranged layers of fine and coarse grains parallel to the laser scanning direction.

thermal gradient

building direction

melt pools

columnar grains

heterogeneously

grains

laser


Input: This unique morphological texture played a dominant factor for the big difference in tensile properties between different loading directions in the early stage of deformation.

texture

tensile properties

deformation


Input: In particular, the alternatively arrangement of fine and coarse grains could generate high hetero-deformation induced (HDI) hardening along the scanning direction in the as-built samples by profuse evolution of geometrically necessary dislocation at the boundaries of each layer.

grains

scanning

samples

evolution

dislocation

hardening

boundaries

layer


Input: On the other hand, upon the last stage of plastic deformation, the crystallographic texture played a crucial role in directional flow behavior by modulating twinning activity.

plastic deformation

texture

twinning


Input: The combined contribution of the various anisotropic microstructural factors to the tensile properties of the SLM-processed HEAs was clarified both qualitatively and quantitatively.

anisotropic

tensile properties

quantitatively


Input: This work will shed light on effective utilization of both heterogeneity and anisotropy of the structural parts for customized performance via expanding multi-scale freedom of design in additive manufacturing.

heterogeneity

performance

anisotropy

design

additive manufacturing


Input: IN625 grains grew epitaxially on the fine grains of SS316L forming Type-I interface.

grains

grains

interface

forming


Input: Bidirectional nucleation from IN625 and mushy zone at SS316L formed Type-II interface.

nucleation

mushy zone

interface


Input: Cracking was formed at Type-II interface and in the SS316L tracks.

Cracking

interface


Input: Cracking mechanisms include solidification, liquidation, and ductility dip cracking.

Cracking

solidification

cracking

ductility


Input: This research illustrates the rationale of adopting a preferred printing sequence by examining crack generation predominated by resultant interfaces and microstructural inhomogeneity, through underlying governing mechanisms in directed energy deposition of 316L stainless steel/Inconel 625 (SS316L/IN625) bimetals.

research

microstructural

directed energy deposition


Input: For this purpose, microstructural and crystallographic characterizations augmented by numerical simulations were employed on additively manufactured two distinct interfaces, i.e.

microstructural

numerical simulations

additively manufactured


Input: Type-I (IN625 deposition on SS316L) and Type-II (SS316L deposition on IN625).

deposition

deposition


Input: Changing the printing sequence generated these two types of interfaces with unique morphologies, which was found attributable to the compositional variations and mismatch in thermal properties.

morphologies

variations

thermal properties


Input: Type-I interface was typified by gradual-change composition in the transition zone, causing the IN625 grains to grow epitaxially on the grains of SS316L.

interface

composition

transition

grains

grains


Input: Type-II interface was characterized as a compositional sudden-change zone (CSCZ) adjacent to SS316L, leading to merging bidirectional nucleation and grain growth from the bottom IN625 and upper CSCZ, and lack of epitaxial growth.

interface

nucleation

grain growth

as

epitaxial


Input: Additionally, high cracking susceptibility occurred near the Type-II interface rather than the Type-I interface, which was related to solidification and liquidation cracking, and further promoted ductility dip cracking.

cracking

interface

interface

solidification

cracking

cracking

ductility


Input: This research will provide a guideline for the additive manufacturing of bimetals with the consideration of printing sequence to control interface formation for a crack-free structure.

research

interface

structure

additive manufacturing


Input: X-ray μCT used for non-destructive measurement of porosity through the multiple stages of the CEAM.

X-ray

measurement

porosity


Input: Porosity was quantified and mapped within the parts by using image analysis.

Porosity

image analysis


Input: Vertical and radial gradient of porosity and pore size observed in green, de-bound and sintered samples.

Vertical

samples

porosity

pore size

sintered


Input: The microscopic and macroscopic quality of samples improves through the process stages.

macroscopic

samples

process


Input: Ceramic Extrusion Additive Manufacturing (CEAM) enables the die-less fabrication of small ceramic parts, with a process chain that includes four consecutive stages: the 3D printing, solvent de-binding, thermal de-binding, and sintering.

Ceramic

ceramic

Additive Manufacturing

fabrication

3D printing

sintering

process chain


Input: The 3D printing process was implemented through Ephestus, a specially developed EAM machine for the manufacturing of parts from alumina feedstock.

3D printing

manufacturing

machine

alumina


Input: A test part was designed, and X-ray computed tomography (μ-CT) was used to quantify its characteristics through the processing stages of the EAM.

designed

X-ray computed tomography


Input: The porosity distribution and the distribution of void size and shape were determined throughout the samples at each stage, using image analysis techniques.

porosity

distribution

distribution

void

samples

image analysis


Input: Furthermore, the evolution of some macroscopic quality properties was measured.The results show that both microscopic (porosity) and macroscopic (geometry, density) properties of the samples improve through the process stages.

evolution

macroscopic

properties

macroscopic

geometry

properties

samples

process

porosity

density


Input: A vertical gradient of porosity is present in green and de-bound samples, with porosity decreasing with increasing sample height.

vertical

samples

sample

porosity

porosity


Input: After sintering, the vertical gradient of porosity disappears.

sintering

vertical

porosity


Input: The sphericity and the diameter of voids are negatively correlated and dispersed over a wide range in the green state.

diameter

voids

correlated

range


Input: The sintering process has a homogenization effect on the void shape distribution.

sintering

homogenization

process

void

distribution


Input: The geometrical deviation from the nominal designed dimensions and the surface quality of parts improves when moving from the green to the sintered state.

designed

surface quality

sintered


Input: Experimental investigation of porosities in additive manufactured ceramics parts.Download: Download high-res image (178 In this paper, the authors explore the use of impedance-based monitoring techniques for in-situ detection of additive manufacturing build defects.

Experimental

high-res image

in-situ

defects

porosities

additive manufactured

additive manufacturing


Input: By physically coupling a piezoceramic (PZT) sensor to the part being fabricated, the measured electrical impedance of the PZT can be directly linked to the mechanical impedance of the part.

PZT

PZT

be

sensor

fabricated

electrical

mechanical


Input: It is hypothesized that one can detect build defects in geometry or material properties in-situ by comparing the signatures collected during printing of parts with that of a defect-free control sample.

build

geometry

material properties

in-situ

sample


Input: In this paper, the authors explore the layer-to-layer sensitivity for both PZT sensors embedded into printed parts and for a fixture-based PZT sensor.

sensitivity

PZT

PZT


Input: For this work, this concept is evaluated in context of material jetting.

material jetting


Input: A set of control samples is created and used to establish a baseline signature.

set

samples


Input: (e.g., internal voids) are fabricated and their layer-to-layer signatures are compared to a control sample.

internal voids

fabricated

sample


Input: Using this technique, the authors demonstrate an ability to track print progress and detect defects as they occur.

print

defects

as


Input: For embedded sensors the defects were detectable at 2.28% of the part volume (95.6 mm3) and by fixture-based sensors when it affected 1.38% of the part volume.

sensors

sensors

defects

volume

volume


Input: Surface roughness of an as produced AM component is very high, which prohibits the direct utilization of additively manufactured (AM) components for the intended applications.

Surface roughness

as

AM

additively manufactured

AM

components


Input: Reducing surface roughness is exponentially more challenging for the internal surfaces of an AM component.

surface roughness

surfaces

AM


Input: This paper reports our research in the area of postprocessing of interior surfaces of an AM component.

research

postprocessing

surfaces

area

AM


Input: We have investigated electropolishing and chemical polishing (chempolishing) methods to reduce the surface roughness of the internal surface.

electropolishing

chemical polishing

surface roughness

surface


Input: We found that chempolishing was effective in simultaneously reducing the internal and external surface roughness of 316 steel AM components.

surface roughness

steel

AM


Input: Chempolishing is found suitable for any complicated AM shape and geometry.

AM

geometry


Input: Our electropolishing methodology was effective in reducing the surface roughness of the internal or external surfaces provided that a counter electrode could be positioned in the proximity of the surface to be polished.

electropolishing

surface roughness

surfaces

surface

electrode

be

be


Input: We have performed optical profilometry, scanning electron microscopy, and contact angle measurement study to investigate the difference between electropolishing and chemical polishing methods.

optical

scanning electron microscopy

measurement

contact

electropolishing

chemical polishing


Input: Modelling of wire-arc additive manufacturing process is an effective way for adapting the optimum parameters as well as understanding and managing the sequences of layer-by-layer deposition.

Modelling

wire-arc additive manufacturing process

parameters

layer-by-layer deposition

as

as


Input: Some of these parameters such as toolpath, deposition intervals and heat source power play important roles in improving the process viability and cost efficiency.

parameters

deposition

heat source

process

as


Input: In this article, we have studied Al-5Mg, Al-3Si alloys as demonstrators, from both experimental and modelling perspectives, to benchmark different deposition parameters and provided guidelines for optimising the process conditions.

alloys

experimental

deposition

process

modelling

benchmark


Input: Physical values such as total distortion and residual stress were selected as indicators for the manufacturability of the structure.

as

as

distortion

manufacturability

structure

residual stress


Input: The simulations were performed by Simufact Welding software, that is outfitted with the MARC solver and the experiments were executed in a robotic cell.

simulations

Welding

software

cell


Input: We have introduced a method for optimising the process parameters based on the heat source power modification and selection of unique parameters for each deposition layer.

process parameters

heat source

parameters

deposition layer


Input: This was performed by monitoring the evolution of the molten pool size and geometry when building a wall structure.

evolution

molten pool

geometry

structure


Input: The results suggest that achieving an uninterrupted deposition process entails modification of the heat input for each layer.

deposition process

heat

layer


Input: Thus, a simple analytical method was proposed to estimate the heat input reduction coefficient for a wall structure as a function of molten pool geometry and the height at which, a new layer is being deposited.

simple

heat

reduction

structure

as

molten pool geometry

layer


Input: It was also shown that a generic selection of parameters for aluminium alloys may impair the eventual quality for some of the alloys due to their inherent physical properties such as high temperature flowability.

parameters

quality

aluminium alloys

alloys

as

physical properties

temperature


Input: In the current investigation, an ultrasonic imaging system originally developed for visualization of microstructures in sheet metals, with capabilities of generating plane two-dimensional images at spatial resolutions between 1 and 200 μm, was used to quantitatively evaluate a Fused Filament Fabrication (FFF) processed 3D test part.

imaging

microstructures

sheet metals

two-dimensional images

quantitatively

processed 3D

Fused Filament Fabrication

FFF


Input: For the ultrasonic system, a custom software program was written to control all components of the inspection schemes in a continuous scan mode, including the movement of three orthogonal translational stages, as well as display a live ultrasonic image during scanning and provide tools for advanced post-processing of the recorded ultrasonic signals.

software

image

scanning

post-processing

components

tools

inspection

as

as


Input: Prior to collecting ultrasonic data for a selected test specimen, an optical flat reference standard was used to characterize the ultrasonic probes and to quantify the system’ s mechanical stability, repeatability, and accuracy when measuring the physical dimensions of features.

data

standard

repeatability

optical

accuracy

probes

s

mechanical

dimensions


Input: Ultrasonic data collected at different spatial resolutions were used to characterize a part’ s surface flatness, internal defects, and fusion conditions; and to measure the physical dimensions of intended features.

data

defects

fusion

s

flatness

dimensions


Input: Finally, a suggestion is made for adopting a process to qualify or certify FFF based additive manufacturing machines in the market by applying a reliable NDE validation method to a standardized part with various features of different shapes and physical dimensions.

process

validation

FFF

additive manufacturing machines

dimensions


Input: Successful printing of high-performance material with suitable properties using additive manufacturing methods such as Fused Filament Fabrication (FFF) can create many advanced applications in industries.

material

as

Filament

properties

additive manufacturing

Fabrication

FFF

industries


Input: However, the high viscosity of high-performance polymers causes complications during the FFF process and reduces the final print quality.

viscosity

polymers

FFF

print quality


Input: To overcome this challenge, Inorganic Fullerene Tungsten Sulphide (IF-WS2) nanoparticles are applied in this study to enhance the flowability of poly-ether-ketone-ketone (PEEK) without compromising its mechanical and thermal properties.

Fullerene

PEEK

nanoparticles

thermal properties

mechanical


Input: In the first step, different loadings of IF-WS2 nanoparticles are melt compounded with PEEK and the nanocomposites are characterized.

step

nanoparticles

melt

PEEK


Input: SEM and EDX images of fractured surfaces indicate that a good dispersion of nanoparticles is achieved without any pre-treatment or pre-dispersion.

SEM

EDX

surfaces

dispersion

nanoparticles


Input: A reduction in melt viscosity of 25%, and a simultaneous growth in storage modulus, crystallization and degradation temperature of about 60%, 53% and 100 °C is found with addition of 2 wt% IF-WS2 to PEEK, respectively.

reduction

melt

crystallization

degradation

PEEK


Input: This great achievement is mainly ascribed to the unique characteristics of IF-WS2 nanoparticles, acting as both reinforcing and lubricating agents, indicated by a reduction in coefficient of friction.

nanoparticles

reduction

as

coefficient of friction


Input: There is no significant increase of crystallization and melting temperatures with the addition of IF-WS2 nanoparticles, which is beneficial in the FFF process.

crystallization

nanoparticles

melting temperatures

FFF


Input: In the second step, the PEEK nanocomposite filaments are printed via FFF.

step

PEEK

filaments

FFF


Input: The print quality and mechanical properties of the printed PEEK are also improved with the incorporation of IF-WS2 nanoparticles.

print quality

mechanical properties

nanoparticles

PEEK


Input: Hence, incorporation of IF-WS2 nanoparticles into PEEK via melt compounding is an effective approach for the development of suitable high-performance engineering materials for FFF.

nanoparticles

melt

PEEK

engineering materials

FFF


Input: Dislocation structures, chemical segregation, γ′, γ″, δ precipitates, and Laves phase were quantified within the microstructures of Inconel 718 (IN718) produced by laser powder bed fusion additive manufacturing (AM) and subjected to standard, direct aging, and modified multi-step heat treatments.

Dislocation

segregation

Laves phase

standard

precipitates

microstructures

Inconel 718

laser powder bed fusion additive manufacturing

AM

heat treatments


Input: Additionally, heat-treated samples still attached to the build plates vs. those removed were also documented for a standard heat treatment.

heat-treated

heat treatment

build plates

standard


Input: The effects of the different resulting microstructures on room temperature strengths and elongations to failure are revealed.

microstructures

temperature

strengths

failure


Input: Knowledge derived from these process-structure-property relationships was used to engineer a super-solvus solution anneal at 1020 °C for 15 min, followed by aging at 720 °C for 24 h heat treatment for AM-IN718 that eliminates Laves and δ phases, preserves AM-specific dislocation cells that are shown to be stabilized by MC carbide particles, and precipitates dense γ′ and γ″ nanoparticle populations.

solution

Laves

dislocation

heat treatment

cells

be

MC

carbide

precipitates


Input: This “optimized for AM-IN718 heat treatment” results in superior properties relative to wrought/additively manufactured, then industry-standard heat treated IN718: relative increases of 7/10% in yield strength, 2/7% in ultimate strength, and 23/57% in elongation to failure are realized, respectively, regardless of as-printed vs. machined surface finishes.

heat treatment

machined

properties

manufactured

heat

failure

yield strength

ultimate strength

elongation


Input: In this work the effect of manufacturing strategy and post process treatment on the high strain rate (HSR) compressive deformation behavior of additively manufactured powder bed fusion 17-4PH stainless steel is studied.

manufacturing

additively manufactured

bed fusion

process

strain rate

deformation

steel


Input: Specimens were fabricated using three different laser vector path strategies to impart different thermal histories and resulting microstructures in the material.

fabricated

laser

microstructures

material


Input: The effect of post processing in the form of hot isostatic pressing and heat treatment and their effect on HSR compressive deformation response of the material was studied.

post processing

deformation

hot isostatic pressing

heat treatment

material


Input: Defect characteristics were quantified using x-ray micro computed tomography.

Defect

x-ray micro computed tomography


Input: It was found that the laser vector strategy had a strong influence on the development of microstructure and defect characteristics and spatial distribution in the materials which strongly influence the HSR response and the HSR compressive flow stresses of the materials varied by as much as 43% in the regimes tested.

laser

microstructure

defect

materials

materials

spatial distribution

flow stresses

as

as


Input: This work proposes a finite element (FE) analysis workflow to simulate directed energy deposition (DED) additive manufacturing at a macroscopic length scale (i.e.

finite element

workflow

macroscopic

FE

directed energy deposition

DED

additive manufacturing

length scale


Input: part length scale) and to predict thermal conditions during manufacturing, as well as distortions, strength and residual stresses at the completion of manufacturing.

length scale

manufacturing

manufacturing

as

as

strength

residual stresses


Input: The proposed analysis method incorporates a multi-step FE workflow to elucidate the thermal and mechanical responses in laser engineered net shaping (LENS) manufacturing.

FE

mechanical responses

laser engineered net shaping

LENS

manufacturing


Input: For each time step, a thermal element activation scheme captures the material deposition process.

step

element

material

deposition process


Input: Then, activated elements and their associated geometry are analyzed first thermally for heat flow due to radiation, convection, and conduction, and then mechanically for the resulting stresses, displacements, and material property evolution.

elements

geometry

heat

material property

evolution

radiation


Input: Simulations agree with experimentally measured in situ thermal measurements for simple cylindrical build geometries, as well as general trends of local hardness distribution and plastic strain accumulation (represented by relative distribution of geometrically necessary dislocations).

Simulations

in situ

cylindrical

trends

distribution

distribution

dislocations

simple

build

as

as

plastic

hardness


Input: Residual stresses play an important role for the structural integrity of engineering components.

Residual stresses

structural integrity

engineering

components


Input: In this study residual stresses were determined in titanium alloy (Ti-6Al-4V) and Inconel 718 samples produced using selective-laser-melting (SLM) additive manufacturing.

residual stresses

titanium alloy

Inconel 718

SLM

additive manufacturing


Input: The contour method and a numerical simulation approach (inherent-strain-based method) were used to determine the residual stress distributions.

contour

numerical simulation

residual stress

distributions


Input: The inherent-strain-based method reduces the computational time compared to weakly-coupled thermo-mechanical simulations.

thermo-mechanical

simulations


Input: Results showed the presence of high tensile residual stresses at and near the surface of both titanium and Inconel alloys samples, whereas compressive residual stresses were seen at the center region.

tensile residual stresses

residual stresses

surface

titanium

Inconel alloys


Input: A good agreement was seen between the results obtained from contour method and the numerical simulation, particularly 1 mm below the surface of the samples.

contour

numerical simulation

mm

surface

samples


Input: This study presents an automated thresholding method for analyzing and quantifying the internal composition of additive manufacturing (AM) parts using computed tomography (CT) data.

composition

data

additive manufacturing

AM

computed tomography

CT


Input: A mixed skewed-Gaussian distribution (MSGD) algorithm, derived from a statistical image analysis technique called Mixed Gaussian Distribution (MGD) clustering, integrates a mixture of skewed-Gaussian distributions to model the internal phases from CT data.

distribution

algorithm

image analysis

Gaussian

Distribution

distributions

model

CT


Input: The parameters of the MSGD algorithm (i.e.

parameters

algorithm


Input: probability, mean, standard deviation, and skew) are inferred from the measured grayscale histogram using least-squares fitting and are assigned to phases present in the CT data.

probability

standard deviation

CT


Input: From the MSGD fitted and thresholded CT data, phase volume percentages and spatial variations of density of the phases are quantified.

CT

phase

spatial variations

density


Input: The MSGD algorithm was validated using previously reported CT analysis and experimental porosity measurements of two Cobalt Chrome (CoCr) specimens (∼1% and ∼13% porosity) fabricated by powder bed fusion (PBF).

algorithm

experimental

fabricated

CT

Cobalt Chrome

porosity

powder bed fusion

PBF


Input: Compared with the 1.1% and 13.7% porosity of the specimens measured by the Archimedes method, the MSGD method predicted a porosity of 1.6% +/− 0.7% and 14.5% +/− 1.9%, a measured increase of 0.5% and 0.8%, respectively.

porosity

porosity

Archimedes method

predicted


Input: These results show a similarity in predicted porosity between Archimedes and MSGD method indicating that CT and the MSGD method may provide a reasonable estimate for part porosity.

predicted

porosity

porosity

CT


Input: Developed a design and fabrication workflow for DM-based FGM structures.

design

fabrication

FGM


Input: The workflow integrates material as well as structural design with fabrication.

workflow

material

as

as

design

fabrication


Input: Used a simplified regression-based model to predict the mechanical behavior of DMs.

model

mechanical


Input: Experimentally validated the workflow with the help of voxel printed FGM structures.

Experimentally validated

workflow

voxel

FGM


Input: Voxel-based multimaterial jetting additive manufacturing allows fabrication of digital materials (DMs) at the meso-scale (∼1 mm) by controlling the deposition patterns of soft elastomeric and rigid glassy polymers at the voxel-scale (∼90 μm).

multimaterial jetting additive manufacturing

fabrication

mm

digital materials

deposition

polymers


Input: The digital materials can then be used to create heterogeneous functionally graded material (FGM) structures at the macro-scale (∼10 mm) programmed to behave in a predefined manner.

digital materials

heterogeneous

be

functionally graded material

FGM

mm


Input: This offers huge potential for design and fabrication of novel and complex bespoke mechanical structures.This paper presents a complete design and manufacturing workflow that simultaneously integrates material design, structural design, and product fabrication of FGM structures based on digital materials.

design

design

design

structural design

fabrication

manufacturing

fabrication

FGM

mechanical

material

digital materials


Input: This is enabled by a regression analysis of the experimental data on mechanical performance of the DMs i.e., Young’ s modulus, tensile strength and elongation at break.

regression analysis

experimental data

mechanical

s

tensile strength

elongation


Input: This allows us to express the material behavior simply as a function of the microstructural descriptors (in this case, just volume fraction) without having to understand the underlying microstructural mechanics while simultaneously connecting it to the process parameters.Our proposed design and manufacturing approach is then demonstrated and validated in two series of design exercises to devise complex FGM structures.

material

as

microstructural

microstructural

process

volume fraction

design

design

manufacturing approach

FGM


Input: First, we design, computationally predict and experimentally validate the behavior of prescribed designs of FGM tensile structures with different material gradients.

design

designs

FGM

material gradients


Input: Second, we present a design automation approach for optimal FGM structures.

design

automation

FGM


Input: The comparison between the simulations and the experiments with the FGM structures shows that the presented design and fabrication workflow based on our modeling approach for DMs at meso-scale can be effectively used to design and predict the performance of FGMs at macro-scale.

simulations

modeling

FGM

fabrication

design

design

be

performance


Input: Porous titanium and tantalum structures were fabricated by additive manufacturing with 30% volume fraction designed porosity.

Porous

tantalum

fabricated

additive manufacturing

volume fraction

designed


Input: Nanotubes were formed on the surface of the porous titanium using anodization process (TNT).

Nanotubes

surface

porous

anodization

TNT


Input: Porous TNT and porous Ta showed comparable new bone formation as early as 5 weeks after surgery in a rat distal femur model.

Porous

porous

bone

as

as

surgery

model


Input: Our findings for TNT pave a way to avoid high manufacturing cost related to biomedical application of tantalum.

TNT

tantalum

manufacturing cost

biomedical application


Input: Material properties of implants such as volume porosity and nanoscale surface modification have been shown to enhance cell-material interactions in vitro and osseointegration in vivo.

Material properties

implants

as

porosity

osseointegration

surface modification


Input: Porous tantalum (Ta) and titanium (Ti) coatings are widely used for non-cemented implants, which are fabricated using different processing routes.

Porous

Ta

titanium

Ti

coatings

implants

fabricated


Input: In recent years, some of those implants are being manufactured using additive manufacturing.

implants

manufactured

additive manufacturing


Input: However, limited knowledge is available on direct comparison of additively manufactured porous Ta and Ti structures towards early stage osseointegration.

additively manufactured

Ta

Ti

osseointegration


Input: In this study, we have fabricated porous Ta and Ti6Al4V (Ti64) implants using laser engineered net shaping (LENS™) with similar volume fraction porosity to compare the influence of surface characteristics and material chemistry on in vivo response using a rat distal femur model for 5 and 12 weeks.

fabricated

surface

chemistry

model

Ta

material

implants

laser engineered net shaping

volume fraction

porosity


Input: We have also assessed whether surface modification on Ti64 can elicit similar in vivo response as porous Ta in a rat distal femur model for 5 and 12 weeks.

surface modification

as

Ta

model


Input: The harvested implants were histologically analyzed for osteoid surface per bone surface.

implants

surface

bone


Input: Field emission scanning electron microscopy (FESEM) was done to assess the bone-implant interface.

Field emission scanning electron microscopy

FESEM

bone-implant interface


Input: The results presented here indicate comparable performance of porous Ta and surface modified porous Ti64 implants towards early stage osseointegration at 5 weeks post implantation through seamless bone-material interlocking.

performance

porous

porous

osseointegration

surface modified

implantation

implants


Input: Design for Additive Manufacturing (DfAM) allows optimising parts by integrating complexity.

Design for Additive Manufacturing

complexity


Input: DfAM adds value to powder bed fusion (PBF) manufacturing in terms of cost, manufacturing lead time, and productivity.

powder bed fusion

PBF

manufacturing

manufacturing

lead time

productivity


Input: Material usage is the main cost driver in metal PBF and is determined by part volume and lattice volume fraction.

Material

metal

volume

lattice

fraction


Input: DfAM can reduce the manufacturing cost by 53.7%, manufacturing time by 54.3%, and overall weight by 52.5%.

manufacturing cost

manufacturing

weight


Input: DfAM is necessary to increase the economic feasibility of AM business cases.

feasibility

AM


Input: The cost-effectiveness of metal powder bed fusion (PBF) systems in high-throughput production are dominated by the high cost of metallic powder materials.

metal powder bed fusion

PBF

production

metallic powder

materials


Input: Metal PBF technologies become more competitive in production scenarios when Design for Additive Manufacturing (DfAM) is integrated to embed functionality through shape complexity, weight, and material reduction through topology optimization and lattice structures.This study investigates the value of DfAM in terms of unit cost and manufacturing time reduction.

Metal

material

technologies

lattice

investigates

reduction

production

manufacturing

Design for Additive Manufacturing

shape complexity

topology optimization

weight


Input: Input design parameters, such as lattice design-type, part size, volume fraction, material type and production volumes are included in a Design-of-Experiment to model their impact.

design

as

material

volume fraction

production

model

impact


Input: The performance variables for cost and manufacturing time were assessed for two scenarios: (i) outsourcing scenario using an online quotation system, and (ii) in-house scenario utilizing a decision support system (DSS) for metal PBF.The results indicate that the size of the part and the lattice volume fraction are the most significant parameters that contribute to time and cost savings.

performance

outsourcing

lattice

fraction

parameters

manufacturing

support

metal


Input: This study shows that full utilization of build platforms by volume-optimized parts, high production volumes, and reduction of volume fraction lead to substantial benefits for metal PBF industrialization.

build platforms

production

reduction

volume fraction

lead

metal


Input: Integration of DfAM and lattice designs for lightweight part production can decrease the unit cost of production down to 70.6% and manufacturing time can be reduced significantly down to 71.7% depending on the manufacturing scenarios and design constraints when comparing to solid infill designs.

lattice designs

design

designs

lightweight

production

production

manufacturing

manufacturing

be

infill


Input: The study also provides a case example of a bracket design whose cost is reduced by 53.7%, manufacturing time is reduced by 54.3%, and the overall weight is reduced significantly with the use of lattices structures and topology optimization.

bracket

manufacturing

weight

lattices

topology optimization


Input: The capability to manufacture items in space is an exploration enabling advancement, and will be crucial for sustainable human exploration as we progress beyond Earth orbit.

manufacture

sustainable

be

as


Input: The extrusion based Fused Filament Fabrication (FFF) method using thermoplastics represents a robust and simple methodology applicable to printing parts for both current and future human spaceflight exploration missions.

extrusion

Fused Filament Fabrication

FFF

simple

thermoplastics

methodology


Input: Understanding the performance and behaviour of the FFF process under varying gravity loads is therefore an important knowledge gap that needs to be addressed in order to fully appreciate the characteristics of space manufactured elements.

performance

manufactured

FFF

be

elements


Input: In this study, we detail an experiment conducted on a parabolic flight campaign (PFC) wherein we produced a number of FFF polylactic acid (PLA) polymer test articles and compared them to terrestrially fabricated articles.

experiment

fabricated

FFF

PLA

polymer


Input: We report on the methodology and the operational parameters used, as well as presenting an analysis of the samples via optical microscopy and tomography.

methodology

parameters

samples

as

as

optical microscopy


Input: Compressive, tensile and other technical properties are reported herein.

tensile

properties


Input: An approach to teaching additive manufacturing (AM) course for engineering students is suggested.

additive manufacturing

AM

engineering


Input: A pedagogical model was developed, based on PDL strategy, for a 14-week AM course.

model

AM


Input: The students designed and 3D printed devices helping people with disabilities.

designed

3D printed


Input: The projects served as useful collaborative learning experiences for AM education.

as

AM


Input: The course demonstrates the potential of AM technologies as innovative environment.

AM technologies


Input: The present study suggests an approach to teaching a novel additive manufacturing (AM) course for engineering students at the graduate level, developed in 2015 and taught currently at Afeka Academic College of Engineering.

additive manufacturing

AM

engineering

Engineering


Input: The proposed course is dedicated to the fundamentals, methods, materials, standards and industrial applications of AM, and involves introduction lectures, special topic lectures organized with industry and academic experts, laboratory training and final engineering projects.

materials

standards

laboratory

industrial

industry

engineering

AM


Input: The first project proposed by the students was to develop and build an opener for medicine containers; the second was to design and build a device for pouring liquids for people with Parkinson’ s disease; and the third was to design and construct a 3D puzzle for blind or visually impaired people.

build

build

medicine

design

design

s


Input: All three projects were designed with a computer-aided design program and then printed using the ABS material.

designed

computer-aided design

ABS material