Input: This approach has the potential to achieve highly dense WC-Co parts that are net-shaped with some ternary phase and z-direction distortion.

phase

distortion

z-direction


Input: This paper proposes a novel geometric based scanning strategy adopted in the selective laser melting (SLM) manufacturing technology aimed at reducing the level of residual stresses generated during the build-up process.

scanning strategy

process

selective laser melting

SLM

manufacturing technology

residual stresses


Input: A set of computer simulations of the build, based on different scans strategies, including temperature dependent material properties, and a moving heat flux, were performed.

set

computer simulations

material properties

heat flux

build

temperature


Input: The research novelty explores intermittent scan strategies in order to analyze the effect of reduction on heat concentration on the residual stress and deformation.

research

reduction

heat

deformation

residual stress


Input: Coupled thermal-structural computations revealed a significant stress and warpage reduction on the proposed scanning scheme.

stress

warpage reduction

scanning


Input: Different powder material properties were investigated and the computational model was validated against published numerical and experimental studies.

powder material

computational model

experimental


Input: This study focuses on the microstructural evolution in additively manufactured (AM) β titanium alloys due to solid-state phase transformations occurring during the reheating of previously deposited layers, directly influencing the uniformity of microstructure across the entire build.

microstructural evolution

solid-state phase

microstructure

additively manufactured

AM

titanium alloys

deposited layers

build


Input: During the AM of titanium alloys of a wide variety of compositions, including α + β alloys such as Ti-6Al-4 V, and β alloys, when the laser or electron beam hits the sample, the grains in the previously deposited topmost layers either re-melt or transform into the β phase.

AM

titanium alloys

alloys

as

V

alloys

laser

electron beam

sample

grains

phase


Input: Subsequently, during the cooling cycle, depending on the alloy composition, second-phase precipitation may occur within these layers via solid-state precipitation.

cooling

alloy

precipitation

solid-state precipitation


Input: The present study compares two binary β -Ti alloys, Ti-12Mo and Ti-20 V, that have been processed using laser engineered net shaping (LENS™), a directed energy deposition technique for AM.

binary

processed

alloys

V

laser engineered net shaping

directed energy deposition

AM


Input: Compared to Ti-V, which exhibited grains of only the β phase in the as-built condition, the less β stabilized Ti-Mo had extensive second-phase α precipitation within the build.

grains

phase

precipitation

build


Input: The location within the LENS™ build played a pivotal role in determining the size scale, area fraction, and morphology of the α precipitates.

build

area

morphology

precipitates


Input: These changes have been attributed to the different thermal cycles experienced during the deposition process.

thermal cycles

deposition process


Input: Irrespective of the alloy composition, columnar grains were observed in the depositions with a strong [001] β texture along the build direction.

alloy

columnar grains

texture

build direction


Input: In the Ti-12Mo alloy, wherein second phase α precipitation takes place, there was no significant α texturing, with all twelve variants forming.

alloy

phase

precipitation

forming


Input: Significant attention has been focused on modeling of metallic additive manufacturing (AM) processes, with the initial aim of predicting local thermal history, and ultimately structure and properties.

modeling

metallic additive manufacturing

AM

processes

structure

properties


Input: Existing models range greatly in physical complexity and computational cost, and the implications of various simplifying assumption often go unassessed.

range

complexity

go


Input: In the present work, we first formulate a fast acting Discrete Source Model (DSM) capable of handling the complex processing often encountered in metal powder bed fusion AM.

Source

Model

metal powder bed fusion

AM


Input: We then assess implications of the source representation, details of the numeric implementation, as well as effects of boundary conditions and thermophysical parameters.

source

as

as

boundary conditions

parameters


Input: While a number of approximations limit its quantitative accuracy, the inexpensive nature and ability to treat complex processing plans suggests it will be useful for screening and identification of regions experiencing anomalous thermal history.

limit

quantitative

accuracy

be


Input: Electron beam welding (EBW) is a high-density energy (low heat input) welding technique, resulting in a narrow heat affected zone (HAZ), causing minimal metallurgical changes in the workpieces.

Electron beam welding

EBW

welding

heat

heat affected zone

HAZ

metallurgical


Input: The present research work investigates EB autogenous welded AlSi10Mg samples, produced by the selective laser melting (SLM) additive manufacturing (AM) method, with emphasis on the characterization of the joint's macro- and microstructure.

research

investigates

joint

microstructure

welded

selective laser melting

SLM

additive manufacturing

AM


Input: When comparing the EB welded AM parts to the EB welded cast samples two main differences were observed: weld metal porosity and a negligible HAZ in the AM joints and low porosity level but substantial HAZ in the welded cast parts.

welded

welded cast

AM

welded cast

AM parts

samples

HAZ

HAZ

weld metal

porosity

porosity


Input: These preliminary results show for the first time the feasibility of the EBW technique on AM-SLM specimens.

feasibility

EBW


Input: The material extrusion additive manufacturing technique known as fused filament fabrication (FFF) is an interesting method to fabricate complex ceramic parts whereby feedstocks containing thermoplastic binders and ceramic powders are printed and the resulting parts are subjected to debinding and sintering.

material extrusion additive manufacturing

fabrication

FFF

fabricate

sintering

as

filament

ceramic

feedstocks

thermoplastic binders

ceramic powders

debinding


Input: A limiting factor of this process is the debinding step, usually done thermally.

process

debinding


Input: Long thermal cycles are required to avoid defects such as cracks and blisters caused by trapped pyrolysis products.

thermal cycles

defects

as

pyrolysis


Input: The current study addresses this issue by developing a novel FFF binder formulation for the production of zirconia parts with an intermediate solvent debinding step.

FFF

production

binder

zirconia

debinding


Input: Different unfilled binder systems were evaluated considering the mechanical and rheological properties required for the FFF process together with the solvent debinding performance of the parts.

binder

mechanical

rheological properties

FFF

debinding


Input: Subsequently, the same compounds were used in feedstocks filled with 47 vol.% of zirconia powder, and the resulting morphology was studied.

feedstocks

zirconia powder

morphology


Input: Finally, the most promising formulation, containing zirconia, styrene-ethylene/butylene-styrene copolymer, paraffin wax, stearic acid, and acrylic acid-grafted high density polyethylene was successfully processed by FFF.

zirconia

copolymer

paraffin

acrylic

high density polyethylene

processed

FFF


Input: After solvent debinding, 55.4 wt.% of the binder was dissolved in cyclohexane, creating an interconnected porosity of 29 vol.% that allowed a successful thermal debinding and subsequent pre-sintering.

debinding

binder

porosity

thermal debinding

pre-sintering


Input: The layered structure of Additive Manufacturing processes results in a stair- stepping effect of the surface topographies.

layered structure

surface topographies

Additive Manufacturing processes


Input: In general, the impact of this effect strongly depends on the build angle of a surface, whereas the overall surface roughness is additionally caused by the resolution of the specific AM process.

impact

surface

build

resolution

surface roughness

AM process


Input: The aim of this work is the prediction of the surface quality in dependence of the building orientation of a part.

prediction

surface quality

building orientation


Input: These results can finally be used to optimize the orientation to get a desired surface quality.

be

orientation

surface quality


Input: As not all parts of the component surface are equally important, a preselection of areas can be used to improve the overall surface quality of relevant areas.

As

be

component

areas

surface quality

areas


Input: The model uses the digital AMF format of a part.

model

AMF


Input: Each triangle is assigned with a roughness value and by testing different orientations the best one can be found.

roughness value

testing

orientations

be


Input: This approach needs a database for the surface qualities.

database

surface qualities


Input: This must be done separately for each Additive Manufacturing process and is shown exemplarily with a surface topography simulation for the laser sintering process.A validation of the model is done with a monitor bracket of EOS GmbH.

be

Additive Manufacturing process

laser sintering

surface topography

validation

model

monitor

simulation

bracket

EOS GmbH


Input: Measurements of five different orientations of the part, optimized according selected surface areas, show a good accordance between the real surface roughness and the predicted roughness of the simulation.

orientations

predicted

surface areas

surface roughness

simulation


Input: 3D printing using the materials extrusion additive manufacturing (ME-AM) process is highly nonisothermal.

3D printing

materials extrusion additive manufacturing

ME-AM

process


Input: In this process, a solid polymer filament is mechanically drawn into a heated hot end (liquefier) where the polymer is ideally melted to a viscous liquid.

process

melted

polymer filament

polymer

hot end


Input: This melt is extruded through an orifice using applied pressure of the solid filament that is continuously being drawn into the extruder.

melt

pressure

extruded

filament

extruder


Input: The extruded filament melt is deposited to build up the desired part.

extruded

melt

build


Input: The poor thermal conductivity of most polymers inevitably leads to temperature gradients, in both the radial and axial directions.

thermal conductivity

polymers

temperature gradients


Input: Here we quantify the temperature evolution of the polymer filament in axial direction using embedded fine thermocouples as a function of process parameters.

temperature

evolution

process parameters

polymer filament

as

thermocouples


Input: Information about the radial gradients is obtained by introducing dye markers within the filament through understanding the flow behavior through the extruder by the deformation of the dye from a linear to pseudo parabolic profile.

filament

extruder

deformation

profile


Input: The polymer is heated above the glass transition temperature for less than 30 s for reasonable print conditions with the center of the filament remaining cooler than the liquefier temperature throughout the process.

polymer

s

filament

glass transition temperature

process

print

temperature


Input: These process measurements provide critical data to enable improved simulation and modeling of the ME-AM process and the properties of the printed parts.

process

data

properties

simulation

modeling

ME-AM


Input: Dendrites built from elongated cells lead to a dislocation cell structure After a solution heat treatment the dislocation density is significantly decreased Nitrided AM structures can be built to match the properties of conventional 316 L A solution treatment prevents CrN precipitation by eliminating stress A solution treatment plus nitriding are beneficial for corrosion and wear properties Due to the limited wear and corrosion properties of the austenitic stainless steel AISI 316 L, some applications require the benefits of nitriding.

Dendrites

cells

cell

dislocation

properties

corrosion

wear properties

wear

solution heat treatment

Nitrided

AM

solution treatment

solution treatment

nitriding

nitriding

dislocation density

stress

corrosion properties

be

CrN

austenitic stainless steel


Input: The aim of this work was to investigate whether the same positive effect of nitriding could be obtained for 316 L that was additive manufactured using the laser powder-bed fusion process and further solution treated at 1060 °C for 30 min, low-temperature plasma nitrided at 430 °C or both.

nitriding

additive manufactured

plasma nitrided

be

laser

fusion

solution


Input: This study was designed to better understand the additive-manufactured and solution-treated microstructures as well as developing a nitride and a diffusion layer.

designed

microstructures

as

as

nitride

diffusion


Input: The comparison of the wear and corrosion resistance, the microhardness and the microstructure changes of the additive-manufactured steel in different post-treated conditions with a commercial steel was carried out.

wear

corrosion resistance

microhardness

microstructure

steel

steel


Input: It was found that the post-treated low-temperature plasma nitriding improves the wear and corrosion resistance of the additive-manufactured samples.

plasma nitriding

wear

corrosion resistance

samples


Input: The obtained values are similar to the values of conventionally fabricated and nitrided 316 L. The solution treating itself (without further nitriding) did not have any significant impact on these properties.

fabricated

solution

impact

properties

nitrided

nitriding


Input: It was possible to explain the microstructure at the nano level as well as correlating the wear and corrosion properties.

microstructure

wear

nano

as

as

corrosion properties


Input: Control of laser power to improve part quality is critical for fabrication of complex components via Laser Powder Bed Fusion (LPBF) additive manufacturing (AM) processes.

laser power

quality

processes

fabrication

Laser Powder Bed Fusion

LPBF

additive manufacturing

AM

components


Input: If the laser power is too low, it will result in a small melt pool and lack of fusion; on the other hand, if the laser power is too high, it will result in keyhole and material evaporation.

laser power

laser power

melt pool

material

fusion

evaporation


Input: This paper examines a model-based feed-forward control for laser power in LPBF to improve build quality by avoiding the onset of keyhole formation or reducing over-melting.

laser power

build

LPBF


Input: First, an analytical, control-oriented model on the dynamics of melt-pool cross-sectional area in scanning a multi-track part was developed, and then a nonlinear inverse-dynamics controller was designed to adjust laser power such that the melt-pool cross-sectional area can be regulated to a constant set point during the build process.

model

scanning

area

laser power

area

build

controller

designed

be

set


Input: The resulting control trajectory on laser power from the simulated closed-loop controller was then implemented in a LPBF process as a feed-forward (FF) controller for laser power.

laser power

laser power

closed-loop controller

controller

LPBF

as


Input: Multiple bead-on-plate samples of Inconel 625, with different number of tracks and track lengths, were then built on an EOSINT M 280 AM system to evaluate the performance of the resulting FF-Analytic controller.

samples

performance

Inconel 625

AM

controller


Input: Experimental results demonstrated that the proposed FF-Analytic control of laser power was able to avoid the onset of keyhole formation that occurred under a constant laser power for certain samples.

Experimental

samples

laser power

laser power


Input: Furthermore, the proposed FF-Analytic control was demonstrated to have significantly reduced over-melting at the returning ends of the laser scan path in scanning a multi-track part compared to applying a constant laser power, albeit with some over-compensation due to modeling imperfection.

laser scan

modeling

scanning

imperfection

laser power


Input: Overall, the proposed FF-Analytic control of laser power had 23–40% lower average error rate than applying a constant laser power in regulating the melt-pool cross-sectional area to a constant reference value, in terms of measurements of cross-sections at track ends.

laser power

laser power

area

average

cross-sections


Input: Forming quality was compared for AM-built-IN718 samples using two types of powders.

Forming

samples

powders


Input: Samples built with imperfect spherical powders tend to be porous and uneven.

Samples

spherical

powders

be


Input: Processing with spherical powders has a broad process window suppressing defect.

spherical

process

defect

powders


Input: High cooling and solidification rates suppress the interdendritic void formation.

cooling

solidification rates

void


Input: The characteristics of powder applied in electron beam powder-bed fusion (EB-PBF) play a vital role in the process stability and final part performance.

powder

electron beam

fusion

process

performance


Input: We use two types of Inconel 718 alloy powders for experiments, namely, (i) imperfect spherical and (ii) spherical powders.

Inconel 718 alloy

powders

spherical

spherical


Input: They have similar particle size distributions but are different in geometry and built-in defect.

particle size distributions

geometry

defect


Input: The forming qualities concerning surface topography, density, and internal defect of the EB-PBF-built samples prepared using two types of powders are characterized under the same processing conditions.

forming

surface topography

defect

samples

density

powders


Input: In particular, the forming qualities are further compared under the optimal process condition to highlight the decisive role of powder features.

forming

optimal process

powder


Input: Notably, different powder geometries with distinct surface feature inevitably affect the heat transfer during melting.

powder

geometries

surface

heat transfer

feature

melting


Input: The significance of powder feedstock characteristics in defect suppression is clarified with the aid of numerical simulations.

powder feedstock

defect

numerical simulations


Input: The experimental results show that compared to spherical powders, fabrication using imperfect spherical powders is more likely to evoke lack–of–fusion and excessive melting under low and high energy conditions, respectively.

experimental

spherical

spherical

powders

powders

fabrication

melting


Input: Thus, spherical powders have a broader process window in ensuring a higher density and smoother surface than that of imperfect spherical powders.

spherical

process

surface

spherical

powders

powders

density


Input: Moreover, in the sample built with spherical powders, the high cooling and solidification rates evaluated by numerical simulations result in the suppression of the interdendritic voids.

sample

spherical

voids

powders

cooling

solidification rates

numerical simulations


Input: The use of feedstocks from metal injection molding (MIM) for the additive manufacturing (AM) of green parts, which are then debound and sintered in a process called shaping, debinding, and sintering (SDS), is promising in terms of production costs of metallic parts.

feedstocks

metal injection molding

additive manufacturing

AM

sintered

shaping

sintering

green parts

process

debinding

production costs

metallic parts


Input: However, in order to use the cost-efficient AM technique fused filament fabrication (FFF) for SDS, powder-binder mixtures known for MIM feedstocks must be adapted to filament requirements resulting in adjustments to debinding and sintering.

AM technique

fabrication

FFF

sintering

filament

feedstocks

be

filament

debinding


Input: In contrast to FFF, screw-based material extrusion is capable of processing already available MIM feedstocks, but machine costs are high due to complex print heads.

FFF

material extrusion

feedstocks

machine

print heads


Input: In this work, a new process called piston-based feedstock fabrication (PFF) is developed for processing already available MIM feedstocks at comparable costs to FFF.

process

feedstock

feedstocks

fabrication

FFF


Input: First, the state of the art is reviewed highlighting the potential of piston-based material extrusion for its usage in SDS.

art

material extrusion


Input: Experimental studies are performed to validate the developed PFF printer.

Experimental

printer


Input: As material, a Ti-6Al-4V MIM feedstock is used.

As

feedstock


Input: Thresholds for piston speed (0.175 mm/min), extrusion temperature (80 °C), and nozzle diameter (0.4 mm) are determined to ensure a viscosity that allows to control the extrusion process via steps per mm.

piston

extrusion

mm

extrusion process

mm

nozzle diameter

viscosity


Input: With these thresholds it is found that a constant extrusion process can be established in a filling range of the cylinder up to 155 mm.

extrusion process

mm

be

range


Input: Finally, the performance of the PFF system is evaluated in terms of nozzle geometry, print speed, and reproducibility showing that reproducible green part properties are achieved at a maximum speed of 8.18 mm/s while using a tapered FFF nozzle.

performance

geometry

reproducibility

nozzle

print

FFF

green part


Input: A thermo-mechanical model of directed energy deposition additive manufacturing of Ti–6Al–4V is developed using measurements of the surface convection generated by gasses flowing during the deposition.

thermo-mechanical model

surface

deposition

directed energy deposition additive manufacturing


Input: In directed energy deposition, material is injected into a melt pool that is traversed to fill in a cross-section of a part, building it layer-by-layer.

directed energy deposition

material

melt pool

layer-by-layer


Input: This creates large thermal gradients that generate plastic deformation and residual stresses.

thermal gradients

plastic deformation

residual stresses


Input: Finite element analysis (FEA) is often used to study these phenomena using simple assumptions of the surface convection.

Finite element analysis

surface

simple


Input: This work proposes that a detailed knowledge of the surface heat transfer is required to produce more accurate FEA results.

surface

heat transfer

accurate


Input: The surface convection generated by the deposition process is measured and implemented in the thermo-mechanical model.

surface

thermo-mechanical model

deposition process


Input: Three depositions with different geometries and dwell times are used to validate the model using in situ measurements of the temperature and deflection as well as post-process measurements of the residual stress.

geometries

model

in situ

dwell times

temperature

as

as

residual stress


Input: An additional model is developed using the assumption of free convection on all surfaces.

model

surfaces


Input: The results show that a measurement-based convection model is required to produce accurate simulation results.

model

accurate


Input: Easily segregated Cu-15Ni-8Sn alloy bulk material was fabricated using a selective laser melting (SLM) process.

alloy

material

fabricated

process

selective laser melting

SLM


Input: The microstructure of SLM-manufactured Cu-15Ni-8Sn alloy was investigated using optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffraction (XRD), and transmission electron microscopy (TEM).

microstructure

alloy

optical microscopy

OM

scanning electron microscopy

SEM

X-ray diffraction

XRD

transmission electron microscopy

TEM


Input: Differences in the microstructures and elemental segregation of gas-atomized alloy powder, cast ingots, and SLM-manufactured samples were analyzed.

microstructures

alloy

segregation

samples

cast


Input: The statistical average grain size of the SLM-manufactured Cu-15Ni-8Sn alloy was 4.03 μm.

average

alloy


Input: Microstructures of the SLM-manufactured sample were mainly composed of epitaxially grown slender cellular structures with submicron widths.

Microstructures

sample

cellular structures


Input: Microsegregation was detected by TEM, and 80- to 200-nm Sn-enriched precipitates were dispersed between cellullar structures.

Microsegregation

TEM

precipitates


Input: Many dislocations and dislocation tangles appeared around the precipitates.

dislocations

dislocation

precipitates


Input: An EBSD test revealed that most local misorientations within 3 degrees were concentrated in fusion line regions.

EBSD

fusion


Input: Compared with cast ingots, the yield strength Rp0.2, ultimate tensile strength Rm, elongation A, and elastic modulus E of the SLM-manufactured sample increased by 67%, 24.6%, 360%, and 7%, respectively.

cast

yield strength

ultimate tensile strength

elongation

elastic modulus

sample


Input: Moreover, the SLM-manufactured Cu-15Ni-8Sn alloy could be directly aged at 350℃ for 12 h, reaching Rm = 991.1 MPa and A =3%, with no need for solid solution treatment or cold working.

alloy

be

solid solution

MPa

cold working


Input: A method for modeling the effect of stress relaxation at high temperatures during laser direct energy deposition processes is experimentally validated for Ti-6Al-4V samples subject to different inter-layer dwell times.

modeling

laser

stress relaxation

experimentally validated

samples

temperatures

dwell times

direct energy deposition


Input: The predicted mechanical responses are compared to those of Inconel® 625 samples, which experience no allotropic phase transformation, deposited under identical process conditions.

predicted

mechanical responses

samples

phase

process


Input: The thermal response of workpieces in additive manufacturing is known to be strongly dependent on dwell time.

additive manufacturing

be

dwell time


Input: In this work the dwell times used vary from 0 to 40 s. Based on past research on ferretic steels and the additive manufacturing of titanium alloys it is assumed that the effect of transformation strain in Ti-6Al-4V acts to oppose all other strain components, effectively eliminating all residual stress at temperatures above 690 °C.

dwell times

temperatures

research

steels

titanium alloys

additive manufacturing

strain

strain

residual stress

components


Input: The model predicts that Inconel® 625 exhibits increasing distortion with decreasing dwell times but that Ti-6Al-4V displays the opposite behavior, with distortion dramatically decreasing with lowering dwell time.

model

distortion

distortion

dwell times

dwell time


Input: These predictions are accurate when compared with experimental in situ and post-process measurements.

predictions

experimental

post-process

accurate


Input: The present study demonstrates for the first time a unique UK-designed and built Additive Manufacturing (AM) hybrid system that combines polymer based structural deposition with digital deposition of electrically conductive elements.

Additive Manufacturing

AM

hybrid system

polymer

elements

deposition

deposition

electrically


Input: This innovative manufacturing system is based on a multi-planar build approach to improve on many of the limitations associated with AM, such as poor surface finish, low geometric tolerance and poor robustness.

manufacturing system

build

AM

as

surface finish

geometric tolerance

robustness


Input: Specifically, the approach involves a multi-planar Material Extrusion (ME) process in which separated build stations with up to 5 axes of motion replace traditional horizontally-sliced layer modelling.

Material Extrusion

process

build

layer


Input: The construction of multi-material architectures also involved using multiple print systems in order to combine both ME and digital deposition of conductive material.

construction

multi-material

deposition

print

material


Input: To demonstrate multi-material 3D Printing (3DP) we used three thermoplastics to print specimens, on top of which a unique Ag nano-particulate ink was printed using a non-contact jetting process, during which drop characteristics such as shape, velocity, and volume were assessed using a bespoke drop watching system.

multi-material 3D Printing

print

jetting

thermoplastics

ink

as

volume


Input: Electrical analysis of printed conductive tracks on polymer surfaces was performed during mechanical testing (static tensile and flexural testing and dynamic fatigue testing) to assess robustness of the printed circuits.

Electrical

printed conductive

polymer

mechanical testing

testing

testing

tensile

robustness

dynamic


Input: Both serpentine and straight line patterns were used in the testing of Ag particle loaded ink and they showed very similar resistance changes during mechanical exposure.

testing

particle

exposure

ink

resistance

mechanical


Input: Monitored resistance and stress changed as a function of strain exhibiting hysteresis with more prominent residual strain during stretching and compression cycles and 3-point bending flexural tests of PA and CoPA substrates.

resistance

stress

strain

hysteresis

compression

as

residual

bending

PA


Input: Bare and encapsulated tracks exhibited low electrical resistivity (1–3*10−6 Ω*m), and its change was more rapid on ABS and minor on PA and CoPA when increasing tensile and flexural strain up to 1.2% and 0.8%, respectively.

encapsulated

electrical resistivity

PA

ABS

tensile

strain


Input: Resistance of Ag tracks on ABS also increased rapidly during fatigue testing and the tracks easily fractured during repeated stretching-compression cycles at 1% and 1.2% strain.

Resistance

strain

ABS

fatigue testing


Input: No resistance changes of Ag tracks printed on PA and CoPA were observed at lower strain amplitudes whereas at higher strain amplitudes these changes were the lowest for conductive tracks on CoPA.

resistance

strain

strain

PA


Input: Thermal analyses were conducted to determine the printed material’ s glass transition temperature (Tg), stability and degradation behavior to find the optimum annealing conditions post printing.

Thermal analyses

Tg

material

s

glass transition temperature

degradation

stability

annealing


Input: The novel AM printer has the ability to fabricate fully functional objects in one build, including integrated printed circuitry and embedded electronics.

AM

fabricate

build

embedded electronics


Input: This new technology also gives the opportunity for designers to improve existing products, as well as create new products with the added advantages of geometrically unconstrained 3DP.

technology

as

as


Input: This paper proposes computational models of the direct energy deposition and powder bed fusion processes developed for process control applications.

computational models

direct energy deposition

powder bed fusion processes

process control


Input: Both models are built upon a regression metamodel of heat transfer beneath the laser beam, to which an auxiliary thermal model is added to account for residual heat in track-to-track interactions.

regression

heat transfer

laser beam

model

residual heat


Input: Both models are coupled by taking temperatures predicted with the auxiliary model and incorporating them as initial conditions for metamodel predictions of future laser scans.

temperatures

predicted

model

predictions

as

laser scans


Input: The synergy of the metamodel and the auxiliary model creates a high-fidelity model, which is used to generate training data for a model-free optimal controller.

model

high-fidelity

data

controller


Input: Simulation results prove the capability of the proposed optimal controller to adjust scan speed to control temperature when accounting for track-to-track interactions.

Simulation

controller

scan speed

temperature


Input: One of the serious obstacles preventing wide industrial use of additive manufacturing (AM) in metals and alloys is a lack of materials available for this technology.

industrial

additive manufacturing

AM

metals

alloys

materials

technology


Input: It is particularly true for the Electron Beam Melting (EBM®) process, where only a few materials are commercially available, which significantly limits the use of the method.

Electron Beam Melting

process

materials

limits


Input: One of the dominant trends in AM today is developing processes for technological materials already widely used by other methods and developed for other industrial applications, gaining further advantages through the unique value added by additive manufacturing.

trends

processes

materials

AM

additive manufacturing

industrial


Input: Developing new materials specifically for additive manufacturing that can utilize the properties and specifics of the method in full is still a research and development subject, and such materials are yet far from full scale industrial usage.

materials

properties

research

materials

additive manufacturing

industrial


Input: Stainless steels are widely used in industry due to good mechanical properties, corrosion resistance and low cost of material.

Stainless steels

material

industry

mechanical properties

corrosion resistance


Input: Hence, there is potentially a market for this material and one possible business driver compared with casting for example is that lead times could be cut drastically by utilizing an additive approach for one-off or small series production.

material

be

additive

casting

production

lead times


Input: This paper presents results from the additive manufacturing of components from the known alloy 316L using EBM®.

additive manufacturing

components

alloy


Input: Previously the samples of 316L were made by laser-based AM technology.

samples

AM technology


Input: This work was performed as a part of the large project with the long term aim to use additively manufactured components in a nuclear fusion reactor.

as

additively manufactured

fusion


Input: Components and test samples successfully made from 316L stainless steel using EBM® process show promising mechanical properties, density and hardness compared to its counterpart made by powder metallurgy (hot isostatic pressing, HIP).

Components

samples

process

mechanical properties

316L stainless steel

density

hardness

powder metallurgy

hot isostatic pressing

HIP


Input: As with the other materials made by EBM® process, 316L samples show rather low porosity.

As

materials

process

samples

porosity


Input: Present paper also reports on the hierarchical microstructure features of the 316L material processed by EBM® characterized by optical and electron microscopy.

microstructure

material

optical

electron microscopy


Input: Roles of heat treatment and build direction are analyzed for SLM IN718.

heat treatment

SLM

build direction


Input: The strength and anisotropic characteristics is explained via microstructure.

strength

anisotropic

microstructure


Input: High resolution tomography displays the prevalence of near surface porosity.

High resolution

surface

porosity


Input: Strain partitioning is observed based on the γ’’ precipitates diffraction spots.

Strain

precipitates

diffraction


Input: The benefits of additive manufacturing have been well documented, but prior to these materials being used in critical applications, the deformation mechanisms must be properly characterized.

additive manufacturing

materials

deformation

be


Input: In this work, the role of heat treatment and build orientation of selective laser melting IN718 is investigated through detailed characterization.

heat treatment

selective laser melting

build orientation


Input: The microstructure of this material is probed through a combination of electron microscopy to identify the precipitate structure, electron backscatter diffraction to quantify the grain-level features, and synchrotron-based X-ray microcomputed tomography to detect porosity.

microstructure

material

precipitate

electron microscopy

electron backscatter diffraction

X-ray

porosity


Input: A high degree of porosity is observed spatially near the free surface of the part, where the contour during the build process meets the interior hatch.

porosity

free surface

contour

build


Input: Further, microstructure based deformation mechanisms are explored through digital image correlation relative to the grain features after monotonic and cyclic loading and in situ high-energy X-ray diffraction to identify the lattice strain evolution in these materials.

microstructure

deformation

digital image correlation

grain

in situ

lattice

evolution

materials

cyclic loading

X-ray diffraction


Input: Demarcations between the behaviors of the as-built versus post-processed materials are discussed; specifically, in terms of anisotropy with respect to build direction and values of the strength properties, based on the grain morphology, coherent twin formation, and precipitate structure.

materials

grain

anisotropy

strength properties

build direction

precipitate


Input: Lastly, the presence of dislocation sub-structures within the grains is observed to homogenize deformation within the as-built sample, while strain partitioning is observed during loading of the post-processed sample.

dislocation

grains

deformation

sample

sample

strain


Input: A process is presented for the rapid production of microstructured monofilaments via thermal drawing of additively manufactured polymer preforms.

process

production

drawing

additively manufactured


Input: Preforms are produced wholly, or in part, via fused filament fabrication of acrylonitrile-butadiene-styrene (ABS) and polycarbonate materials.

fused filament fabrication

ABS

polycarbonate

materials


Input: Example monofilaments include “microprinted” monofilaments that contain an arbitrary image embedded in the monofilament cross section; microfluidic monofilaments in which flow channels are formed by combining optically transparent and opaque materials; dual-material monofilaments that combine ABS and polycarbonate into a regular spoked geometry with five-fold symmetry; and a microfluidic preform co-fed with glass optical fiber, allowing both fluid and light transmission through the monofilament.

image

cross section

transparent

materials

dual-material

geometry

ABS

polycarbonate

glass

fiber

fluid

transmission


Input: The primary advantages of this monofilament fabrication technique include short lead times; minimal investment in materials and equipment; a means of directly combining multiple materials into a single monofilament, even if the material components have different thermorheological properties; and the ability to create arbitrary and complex geometries.

fabrication

lead times

materials

materials

properties

complex geometries

equipment

components

material


Input: Energy system components with embedded sensors, or smart parts, can be a pathway in obtaining real-time system performance feedback and in situ monitoring during operation.

components

sensors

be

performance

in situ

feedback


Input: Traditional surface contact or cavity placed sensors increase the possibility of disturbing the normal operation of energy systems due to changes in part design required for sensor placement.

surface

contact

sensors

sensor

design


Input: The fabrication of smart parts using additive manufacturing (AM) technology can allow the flexibility of embedding a sensor within a structure without compromising the structure and/or functionality.

fabrication

additive manufacturing

AM

technology

structure

structure

flexibility

sensor


Input: The embedding of a sensor within a desired location allows an end user the ability to monitor specific critical regions that are of interest such as high temperature and pressure (e.g., combustor inlet conditions that can reach up to 810 K and 2760 kPa).

sensor

inlet

monitor

pressure

as

K

temperature


Input: In addition, the non-intrusive placement of the sensor within a part’ s body can increase the sensor’ s life span by isolating the sensor from the aforementioned harsh operating environments.

sensor

sensor

sensor

s

s

isolating


Input: This paper focuses on the fabrication of smart parts using electron beam melting (EBM) AM technology as well as the characterization of the sensor’ s functionality.

fabrication

electron beam melting

EBM

AM technology

as

s

sensor


Input: The development of a “stop and go” process was explored that comprised of pausing a part’ s fabrication process to allow the placement of piezoelectric ceramic material into pre-designed cavities within a part’ s body, and resuming the process to complete the final product.

go

s

ceramic material

s

process

process

fabrication


Input: A compression test was performed on the smart parts fabricated using EBM to demonstrate the sensor’ s capability of sensing external forces.

compression test

fabricated

forces

EBM

sensor

s

sensing


Input: A maximum sensing voltage response of approximately 3 V was detected with a maximum pressure not exceeding 40 MPa.

sensing

V

pressure

MPa


Input: This research work demonstrates the feasibility of fabricating smart parts with embedded sensors without the need of post-processing (e.g., CNC machining and polishing).

research

feasibility

post-processing

fabricating

CNC machining

polishing

sensors


Input: In addition, the sensing capability of monitoring a component’ s performance has been validated, leading to the possibility of fabricating other smart parts that could impact industries such as energy, aerospace, automotive, and biomedical industries for applications like air/fuel pre-mixing, pressure tubes, and turbine blades.

sensing

aerospace

automotive

biomedical industries

turbine blades

component

s

as

performance

impact

fabricating

pressure tubes


Input: Recycling metal powders in the Additive Manufacturing (AM) process is an important consideration in affordability with reference to traditional manufacturing.

Recycling

process

metal powders

Additive Manufacturing

AM

traditional manufacturing


Input: Metal powder recyclability has been studied before with respect to change in chemical composition of powders, effect on mechanical properties of produced parts, effect on flowability of powders and powder morphology.

Metal powder

powders

powders

powder

chemical composition

mechanical properties

morphology


Input: In this paper, we propose a data-driven method to understand in situ behavior of recycled powder on the build platform.

in situ

recycled

powder

build platform


Input: Our method is based on comprehensive analysis of log file data from various sensors used in the process of printing metal parts in the Arcam Electron Beam Melting (EBM) ® system.

file

data

process

sensors

metal

Electron Beam Melting

EBM


Input: Using rake position data and rake sensor pulse data collected during Arcam builds, we found that Inconel 718 powders exhibit additional powder spreading operations with increased reuse cycles compared to Ti-6Al-4V powders.

data

data

sensor

builds

Inconel 718

powder

Ti-6Al-4V powders


Input: We substantiate differences found in in situ behavior of Ti-6Al-4V and Inconel 718 powders using known sintering behavior of the two powders.

in situ

Inconel 718

powders

sintering


Input: The novelty of this work lies in the new approach to understanding powder behavior especially spreadability using in situ log file data that is regularly collected in Arcam EBM® builds rather than physical testing of parts and powders post build.

powder

powders

in situ

data

file

builds

testing

build


Input: In addition to studying powder recyclability, the proposed methodology has potential to be extended generically to monitor powder behavior in AM processes.

powder

be

methodology

monitor

AM processes


Input: Selective laser melting (SLM) provides an economic approach to manufacturing Ni-base superalloy components for high-pressure gas turbines as well as repairing damaged blade sections during operation.

Selective laser melting

SLM

manufacturing

components

gas turbines

as

as


Input: In this study, two advanced processing routes are combined: SLM, to fabricate small specimens of the nonweldable CMSX-4, and hot isostatic pressing (HIP) with a rapid cooling rate as post-processing to heal defects while the target γ/γ´ microstructure is developed.

SLM

fabricate

hot isostatic pressing

HIP

cooling rate

as

defects

microstructure


Input: An initial parametric study is carried out to investigate the influence of the SLM process parameters on the microstructure and defects occurring during SLM.

SLM

SLM

process parameters

microstructure

defects


Input: Special emphasis is placed on understanding and characterizing the as-built SLM microstructures by means of high-resolution characterization techniques.

SLM

microstructures

high-resolution


Input: The post-processing heat treatment is then optimized with respect to segregation and the γ/γ´ microstructure.

post-processing heat

segregation

microstructure


Input: This article proposes a new method for reducing the amount of support material required for 3-D printing of complex designs generated by topology optimization.

support material

designs

topology optimization


Input: This procedure relies on solving sequentially two structural optimization problems–the first on a discrete truss-based model and the second on a continuum-based model.

structural optimization

model

model


Input: In the optimization of the discrete model, the maximum overhang limitation is imposed based on geometrical parameters.

optimization

model

parameters

overhang


Input: The optimized discrete pattern is then projected on to the continuum so that it influences the material distribution in the continuum optimization.

pattern

continuum

distribution

continuum

material


Input: Numerical results indicate that the designs obtained by this approach exhibit improved printability as they have fewer overhanging features.

designs

overhanging features

printability

as


Input: In some cases, practically no supporting material will be required for printing the optimized design.

material

be

design


Input: The importance of additive manufacturing (AM) to the future of product design and manufacturing infrastructure demands educational programs tailored to embrace its fundamental principles and its innovative potential.

additive manufacturing

AM

manufacturing

product design


Input: The lectures begin with in-depth technical analysis of the major AM processes and machine technologies, then focus on special topics including design methods, machine controls, applications of AM to major industry needs, and emerging processes and materials.

AM processes

AM

machine

machine

design

industry

processes

materials


Input: In lab sessions, students operate and characterize desktop AM machines, and work in teams to design and fabricate a bridge having maximum strength per unit weight while conforming to geometric constraints.

AM machines

design

fabricate

bridge

strength

weight


Input: In a single semester of the course, teams created prototype machines for 3D printing of molten glass, 3D printing of soft-serve ice cream, robotic deposition of biodegradable material, direct-write deposition of continuous carbon fiber composites, large-area parallel extrusion of polymers, and in situ optical scanning during 3D printing.

prototype

deposition

deposition

in situ

scanning

machines

3D printing

3D printing

extrusion

3D printing

molten glass

continuous carbon fiber

composites

polymers

biodegradable material


Input: Several of these projects led to patent applications, follow-on research, and peer-reviewed publications.

led

patent

research


Input: We conclude that AM education, while arguably rooted in mechanical engineering, is truly multidisciplinary, and that education programs must embrace this context.

AM

mechanical engineering


Input: A novel soft mold casting method for metal part fabrication is developed.

mold

casting

fabrication

metal


Input: The paste can be utilized with direct paste printing and soft mold casting.

be

mold

casting


Input: Three-dimensional metal parts can be obtained with good geometric precision.

Three-dimensional

metal

be

precision


Input: Recently, additive manufacturing (AM) of metals has enjoyed significant advancement.

additive manufacturing

AM

metals


Input: While the mainstream AM methods utilize high-energy power beams to melt metal powders, other low-cost alternatives are also being developed (e.g., direct ink printing).

AM

ink printing

power

melt

powders


Input: In this study, a copper powder-binder paste is developed, which is not only capable to be used for direct printing, but also to be cast using soft molds.

copper

be

be

molds


Input: Dense three-dimensional parts can be obtained by sintering green bodies.

three-dimensional

green bodies

be

sintering


Input: The electrical and mechanical properties of the sintered samples are evaluated by conductivity, hardness measurements and tensile tests, respectively.

electrical

mechanical properties

samples

sintered

conductivity

hardness

tensile tests


Input: The results are comparable to other powder processed copper materials.

powder

copper


Input: The properties of 3-D printed polymeric parts depend significantly on the processing conditions under which they are fabricated.

properties

fabricated


Input: This study aims to determine how the use of low-pressure additive manufacturing (AM) processing conditions, influences the mechanical performance of printed polymeric parts.

additive manufacturing

AM

mechanical


Input: This polymer material extrusion (PME) study was carried out using an open-source desktop printer, under both low pressure (1 Pa) and at atmospheric pressure.

polymer material

extrusion

PME

open-source

pressure

pressure

printer

Pa


Input: The printing study was carried out using acrylonitrile butadiene styrene (ABS), polylactic acid (PLA) and a nylon co-polymer (PA6).

acrylonitrile butadiene styrene

ABS

polylactic acid

PLA

nylon


Input: The resultant polymer parts were compared based on their printed mass, density, volume, porosity, surface energy, ATR-IR analysis and thermal properties (DSC).

polymer

density

porosity

volume

surface

thermal properties

DSC


Input: As expected only minor differences in chemical functionality were observed between parts printed under the two processing pressures.

As

pressures


Input: Under low-pressure printing conditions, the polymer parts exhibited some physical changes, when compared to those, printed under atmospheric conditions, such as an increase in density and a decrease in porosity.

polymer

as

density

porosity


Input: Comparing low-pressure printed type V dog bones (ASTM D-638), with those printed at atmospheric pressure, it was observed that the ABS, PLA and PA6 exhibited an increase in Ultimate Tensile Strength of 9%, 13% and 42% respectively.

V

ABS

PLA

pressure

Ultimate Tensile Strength


Input: It is proposed that the superior mechanical properties obtained for polymers printed under low pressure conditions, may be due to a combination of two factors.

mechanical properties

pressure

polymers

be


Input: These are the reduction in porosity of the printed part and the reduction in heat loss at the printed polymer surface, yielding enhanced bonding between the polymer layers.

reduction

reduction

heat

bonding

porosity

polymer

polymer


Input: In a further printing study carried out at atmospheric pressure in a nitrogen atmosphere, it was also demonstrated that any oxidation of the polymer layers during printing, did not significantly influence the mechanical properties of the resultant printed parts.

pressure

mechanical properties

nitrogen

polymer

oxidation


Input: Additive manufacturing (AM) processes are used to build structural components layer-by-layer.

Additive manufacturing

AM

processes

build

components


Input: Cold spray is considered an AM process, whereby particles impact a substrate at high velocities to generate the deposition layer.

AM process

particles impact

substrate

deposition layer


Input: Effect of spray angles on bonding strength at the cold spray deposit and substrate interface was experimentally investigated.

bonding strength

substrate

interface


Input: The results showed that bonding strength increased with decreasing spray angle from the normal direction (90° spray angle), and the maximum bonding strength was observed at 45° spray angle; however, the deposition efficiency and strength of the bulk deposit material decreased with decreasing spray angle.

bonding strength

bonding strength

strength

deposition

material


Input: 3D finite element modeling of single-particle impact combined with experimental observation of “splat” deposits was conducted to understand bonding process under different spray angles.

impact

experimental

bonding

element


Input: The relationships between parameters contributing bonding formations (e.g., plastic deformation and temperature rise due to impact) and processing parameters (e.g., spray angles, impact velocity, pre-heating temperature) were established and discussed.

parameters

bonding

impact

parameters

impact

plastic deformation

temperature

temperature


Input: These relationships are useful for understanding bonding mechanisms and strengths of deposits sprayed at different angles and can be used to define an optimized spray angle.

bonding mechanisms

strengths

sprayed

be


Input: The modeling results also revealed that increasing particle impact velocity and pre-heating temperature promoted deposit quality, but in different respects.

modeling

particle

impact

quality

temperature


Input: Finally, the influence of different primary accelerating gases (helium vs nitrogen) on the material properties of the deposits was investigated.

helium

nitrogen

material properties


Input: The tensile testing showed that fully dense deposits produced with different gases had similar stiffness and yield strength, but different ductility.

tensile testing

fully dense

stiffness

yield strength

ductility


Input: The particle impact model was further used to explain the different material behaviors, which also demonstrated feasibility to connect the spray parameters and the material properties via modeling for optimizing cold spray process.

particle

impact

feasibility

parameters

material properties

process

material

modeling


Input: Lithography-based additive manufacturing (AM) is increasingly becoming the technology of choice for the small series or single unit production.

additive manufacturing

AM

production

technology


Input: At the TU Vienna a digital light processing (DLP) system was developed for the fabrication of complex technical ceramics, requiring high levels of detail and accuracy.

digital light processing

DLP

fabrication

ceramics

accuracy


Input: The DLP-system used in this study creates a ceramic green part by stacking up layers of a photo-curable resin with a solid loading of around 45 vol.% zirconia.

ceramic

photo-curable resin

zirconia


Input: After a thermal debinding and sintering step the part turns into a dense ceramic and gains its final properties.

thermal debinding

sintering

ceramic

properties


Input: The native resolution of the DLP process depends on the light engine's DMD (digital mirror device) chip and the optics employed.

resolution

DLP

DMD

chip

optics


Input: Currently it is possible to print 3D-structures with a spatial resolution down to 40 μm.

print

resolution


Input: A modification of the light source allows for the customization of the light curing strategy for each pixel of the exposed layers.

light source

curing


Input: This work presents methods to improve the geometrical accuracy as well as the structural properties of the final 3D-printed ceramic part by using the full capabilities of the light source.

accuracy

as

properties

light source


Input: On the one hand, the feasibility to control the dimensional overgrowth to gain resolution below the native resolution of the light engine—a sub-pixel resolution—was evaluated.

feasibility

gain

resolution


Input: Overgrowth occurs due to light scattering and was found to be sensitive to both exposure time and exposed area.

light scattering

exposure

be

area


Input: On the other hand, different light curing strategies (LCSs) and depths of cure (Cd) were used for the 3D-printing of ceramic green parts and their influence on cracks in the final ceramic was evaluated.

curing

cure

Cd

ceramic

ceramic


Input: It was concluded that softstart LCSs, as well as higher values for Cd, reduce cracks in the final ceramic.

as

as

Cd

ceramic


Input: Applying these findings within the 3D-printing process may be another step toward flawless and highly accurate ceramic parts.

be

step

accurate


Input: Direct additive manufacturing of ceramics using melt cast route.

additive manufacturing

cast

ceramics

melt


Input: Fabrication of compositionally gradient ceramic-metal structure in one additive manufacturing operation.

Fabrication

additive manufacturing

ceramic-metal


Input: Characterization and defect analysis of AM processed parts.

defect

AM


Input: Laser Engineered Net Shaping (LENS™), which is a laser based additive manufacturing method, was utilized to fabricate Ti-Al2O3 compositionally graded structures.

Laser Engineered Net Shaping

additive manufacturing

fabricate

laser


Input: The Ti-Al2O3 graded composites consisted of different sections −Ti6Al4V alloy, Ti6Al4V + Al2O3 composites, and pure Al2O3 ceramic.

composites

alloy


Input: After LENS™ processing, microstructural characterization, phase analysis, elemental distribution, and microhardness measurements were performed on the cross sections of Ti-Al2O3 graded composites.

microstructural characterization

phase

distribution

microhardness

cross sections

composites


Input: Each section had their unique microstructures and phases.

microstructures


Input: Moreover, hardness measurements demonstrated that the pure Al2O3 section had the highest hardness of 2365.5 ± 64.7 HV0.3.

hardness

hardness


Input: Conventional ceramic processing requires extensive post-processing including high temperature sintering, which makes it difficult for direct fabrication of metal-ceramic multi-layer structures.

ceramic processing

sintering

fabrication

post-processing

temperature


Input: The results demonstrate that LENS™ can be utilized to process multi-material metal ceramic composites in a single step while maintaining the size, shape and compositional variations based on computer aided design files.

be

metal ceramic

composites

process multi-material

step

variations

computer aided design


Input: Since this is a first-generation work, and limited research results are available in published literature related to LENS™ processing of both metals and ceramics in one operation, the demonstration of this work is expected to inspire future studies on manufacturing of multi-material composites using AM.

research

multi-material

metals and ceramics

composites

manufacturing

AM


Input: A rather simple computational analysis for the thermomechanical simulation of the EBM is presented.

simple

EBM

thermomechanical

simulation


Input: A new model is provided to account the powder bed behaviour during the melting.

model

powder bed

melting


Input: Shrinkage and porosity for both powder and bulk materials are considered.

Shrinkage

materials

porosity

powder


Input: Experimental validations support strongly the effectiveness of the proposed model.

Experimental

effectiveness

model

support


Input: The proposed approach might be useful for other powder-based AM processes as well.

be

AM processes


Input: In this work, an improved but still rather simple computational analysis is presented for a more detailed prediction of Electron Beam Melting (EBM) process outcomes.

simple

Electron Beam Melting

EBM

prediction

process


Input: A fully coupled thermomechanical analysis is developed in which nonlinearities due to the variation of material properties when the material melts are included.

thermomechanical

variation

material properties

material


Input: A new analytical approach is developed to emulate the volume variation of the powder bed during heating and melting.

volume

variation

powder bed

heating

melting


Input: Particularly, the expansion of the powder particles and the porosity reduction within the powder bed are considered simultaneously.

powder particles

porosity

powder bed


Input: The thermal expansion and the shrinkage of solid material during heating and cooling and the stress formation within the solid material are also modelled.

thermal expansion

shrinkage

material

material

heating

cooling

stress


Input: The model can predict the geometrical transformation of the powder into solid material in an efficient way.

model

powder

material


Input: A comparison between experimental and simulated cross-sectional areas of melted single lines is presented.

experimental

melted

areas


Input: Both continues line melting and fractional line melting, multi beam melting, are considered.

melting

melting

beam


Input: The model shows a good ability to provide consistent and accurate forecasts.

model

accurate


Input: The main goal of this work is the adoption of additive manufacturing for the production of inexpensive rare-earth free MnAl-based permanent magnets.

additive manufacturing

production

permanent magnets


Input: The use of more advanced binder-free additive manufacturing technique such as Electron Beam Melting (EBM) allows obtaining fully-dense magnetic materials with advanced topology and complex shapes.

binder-free

materials

topology

additive manufacturing

EBM

as

Beam

complex shapes


Input: We focus on the feasibility of controlling the phase formation in additively manufactured Mn-Al alloys by employing post-manufacturing heat treatment.

feasibility

phase

additively manufactured

heat treatment

alloys


Input: The as-manufactured EBM samples contain 8% of the desired ferromagnetic τ-MnAl phase.

EBM

phase


Input: After the optimized annealing treatment, the content of the τ-phase was increased to 90%.

annealing treatment


Input: This sample has a coercivity value of 0.15 T, which is also the maximum achieved in conventionally produced binary MnAl magnets.

sample

binary

magnets


Input: Moreover, the EBM samples are fully dense and have the same density as the samples produced by conventional melting density.

EBM

melting

fully dense

density

density

as

samples


Input: A modelling strategy is proposed to evaluate the influence of defect morphology on the fatigue limit of additively manufactured Al alloys by: (i) obtaining an x-ray micro-Computed Tomography (μ-CT) 3D image of the material, (ii) computing the Equivalent Inertia Ellipsoid of each individual pore, (iii) modelling the influence of the defect on the fatigue limit through the Defect Stress Gradient (DSG) approach coupled to the Eshelby theory and, (iv) 3D mapping the criticality of each individual defect.

modelling

modelling

defect

3D image

defect

Defect

defect

fatigue

pore

fatigue

additively manufactured

alloys

material

x-ray micro-Computed Tomography


Input: For this fatigue study, an AlSi10Mg alloy was manufactured by laser powder bed fusion using sub-optimal deposition parameters in order to produce large lack-of-fusion defects.

fatigue

AlSi10Mg alloy

manufactured

deposition

defects

laser powder bed fusion


Input: After a T6 heat treatment, tension-compression fatigue tests, with R = −1, were conducted on specimens oriented with their loading axis either parallel or normal to the Z-axis of the additive manufacturing equipment.

heat treatment

additive manufacturing

fatigue tests

Z-axis


Input: Two samples were characterised before μ-CT testing in order to characterise the initial 3D defect population.

samples

testing

population


Input: Each sample was fatigued step by step in order to determine the fatigue limit.

sample

step

step

fatigue


Input: The fracture surface was observed in order to identify the critical defect in the initial μ-CT image.

fracture

defect

image


Input: A comparison with the fatigue results led to the following conclusions: (i) when the longest axis of the defect is perpendicular to the loading axis, modelling the defect as an equivalent inertia prolate ellipsoid gives better results (5% error on the fatigue limit) than modelling it as a simple equivalent sphere (22% error on the fatigue limit), (ii) the prolate ellipsoid is not relevant when the longest axis of the defect is oriented along the loading axis; in this case an oblate equivalent ellipsoid should be used, (iii) the concept of ‘size’ for a complex 3D shaped defect should be linked to the inertia and the loading, (iv) with this approach, surface defects are shown to be more critical than internal ones for fatigue life and, (v) a 3D defect criticality map of the entire sample can be plotted to provide visual feedback on which defects are the most critical for fatigue life.

fatigue

fatigue

fatigue

fatigue life

fatigue life

led

defect

defect

error

error

defect

defect

surface defects

sample

defects

modelling

modelling

as

as

be

be

be

v

be

simple

feedback


Input: In common thermoplastic additive manufacturing (AM) processes, a solid polymer filament is melted, extruded though a rastering nozzle, welded onto neighboring layers and solidified.

thermoplastic

polymer filament

additive manufacturing

AM

extruded

welded

processes

melted

nozzle


Input: The temperature of the polymer at each of these stages is the key parameter governing these non-equilibrium processes, but due to its strong spatial and temporal variations, it is difficult to measure accurately.

temperature

polymer

parameter

processes

variations

accurately


Input: Here we utilize infrared (IR) imaging–in conjunction with necessary reflection corrections and calibration procedures–to measure these temperature profiles of a model polymer during 3D printing.

infrared

calibration

model

IR

reflection

imaging

temperature

profiles

3D printing


Input: From the temperature profiles of the printed layer (road) and sublayers, the temporal profile of the crucially important weld temperatures can be obtained.

temperature

layer

temperatures

profiles

profile

weld

be


Input: Under typical printing conditions, the weld temperature decreases at a rate of approximately 100 °C/s and remains above the glass transition temperature for approximately 1 s. These measurement methods are a first step in the development of strategies to control and model the printing processes and in the ability to develop models that correlate critical part strength with material and processing parameters.

weld

temperature

glass transition temperature

step

model

parameters

measurement

printing processes

strength

material


Input: A novel compulsively constricted wire arc additive manufacturing（CC-WAAM）method was proposed with arc and droplets ejected out of a narrow space.

arc

arc

droplets

additive


Input: Small-size liquid droplets were transferred to previous layer with stable path and direction with low heat input.

droplets

heat

layer


Input: Good shielding and heat preservation for high-temperature liquid droplets as well as the liquid pool were guaranteed by the ejected arc plasma.

heat

droplets

arc

as

as


Input: Uniform and fine microstructures were achieved in the deposited metal using mild steel filler wire in CC-WAAM.

microstructures

metal

mild steel


Input: In order to realize oriented wire and arc additive manufacturing (WAAM) featured by low heat input and small droplets, a novel compulsively constricted WAAM (CC-WAAM) method was proposed and investigated in this paper.

wire and arc additive manufacturing

WAAM

WAAM

heat

droplets


Input: The arc burned between a metallic wire and a tungsten electrode in a narrow-space nozzle.

arc

metallic

tungsten

electrode

nozzle


Input: The proposed technology could provide compulsive constriction for arc plasma and liquid metal droplets using a cubic boron nitride (CBN) ceramic nozzle.

technology

arc

droplets

liquid metal

cubic boron nitride

CBN

ceramic


Input: The surrounding arc was ejected out of the nozzle and offered extra heating and a good shielding environment during the whole manufacturing process.

arc

nozzle

heating

manufacturing process


Input: The arc and metal transfer behaviors could be improved for better performance and higher quality.

arc

performance

quality

metal

be


Input: The economic and efficient new method is expected to solve the challenges faced by traditional WAAM such as excessive heat input and poor geometrical accuracy.

faced

WAAM

as

heat

accuracy


Input: Preliminary experiments showed that the two AM layers produced by the novel method had homogeneous microstructure distribution and fine grains.

AM

homogeneous

distribution

grains


Input: The geometrical dimensions of each layer can be effectively controlled by regulating the travel speed of the torch.

dimensions

layer

be


Input: The wide-range adjustable heat input can effectively control the state of the metallic formation, making it possible to realize an accurate control of the microstructure and properties.

heat

microstructure

properties

metallic

accurate


Input: Residual stress distribution in cold spray microparticles for additive manufacturing is studied.

Residual stress

distribution

additive manufacturing


Input: A simulation model for cold-spray additive manufacturing based on arbitrary Lagrangian–Eulerian method is proposed.

simulation

model

additive manufacturing


Input: The residual stress formation mechanism in cold-spray additive manufacturing is explained in detail.

residual stress

mechanism

additive manufacturing


Input: Cold spray (CS) residual stress was measured by the X-ray diffraction (XRD) and contour methods.

residual stress

X-ray diffraction

XRD

contour


Input: The residual stress components SX and SY, perpendicular to the thickness, have similar distributions and approximately equal magnitudes.

residual stress

components

distributions


Input: Both are compressive on the deposited surface and become tensile inside the structure.

surface

structure

tensile


Input: An advanced simulation model based on the arbitrary Lagrangian–Eulerian (ALE) method was developed to investigate the residual stress distributions in a single CS microparticle and multi-layer CS microparticles and reveal the formation mechanism.

simulation

model

distributions

mechanism

residual stress


Input: The residual stress components SX and SY predicted by the proposed simulation model have the same distribution as shown by the measurements, i.e., compressive on the surface and tensile inside.

residual stress

tensile

components

predicted

model

distribution

surface

simulation

as


Input: As the number of deposition layers increases, the position of maximum tensile stress moves from the substrate to the deposited layers.

As

substrate

deposition layers

tensile stress

deposited layers


Input: The residual stress component SZ in the direction of the deposition thickness shows alternate tensile and compressive distributions in the transverse direction, which is quite different from that of the transverse component.

residual stress

tensile

component

component

deposition

distributions


Input: The present work provides a guideline for effectively tailoring the residual stress in CS parts and thereby improving the fatigue lifetime.

residual stress

fatigue


Input: Because many of the most important defects in Laser Powder Bed Fusion (L-PBF) occur at the size and timescales of the melt pool itself, the development of methodologies for monitoring the melt pool is critical.

defects

Laser Powder Bed Fusion

L-PBF

melt pool

melt pool


Input: This works examines the possibility of in-situ detection of keyholing porosity and balling instabilities.

in-situ

porosity


Input: Specifically, a visible-light high speed camera with a fixed field of view is used to study the morphology of L-PBF melt pools in the Inconel 718 material system.

camera

morphology

L-PBF

Inconel 718


Input: A scale-invariant description of melt pool morphology is constructed using Computer Vision techniques and unsupervised Machine Learning is used to differentiate between observed melt pools.

melt pool

melt pools

Computer Vision

Machine


Input: By observing melt pools produced across process space, in-situ signatures are identified which may indicate flaws such as those observed ex-situ.

melt pools

as

process

in-situ

flaws


Input: This linkage of ex-situ and in-situ morphology enabled the use of supervised Machine Learning to classify melt pools observed (with the high speed camera) during fusion of non-bulk geometries such as overhangs.

in-situ

fusion

geometries

Machine

camera

melt pools

as


Input: The ability to deposit a consistent and predictable solidification microstructure can greatly accelerate additive manufacturing (AM) process qualification.

predictable

microstructure

process

additive manufacturing

AM


Input: Process mapping is an approach that represents process outcomes in terms of process variables.

Process

process

process


Input: In this work, a solidification microstructure process map was developed using finite element analysis for deposition of single beads of Ti-6Al-4V via electron beam wire feed AM processes.

solidification microstructure

process

finite element analysis

deposition

electron beam

beads

feed

AM processes


Input: Process variable combinations yielding constant beta grain size and morphology were identified.

Process

morphology

grain size


Input: Comparison with a previously developed process map for melt pool geometry shows that maintaining a constant melt pool cross sectional area will also yield a constant grain size.

process

geometry

melt pool

melt pool

area

grain size


Input: Additionally, the grain morphology boundaries are similar to curves of constant melt pool aspect ratio.

grain

boundaries

aspect ratio

melt pool


Input: Experimental results support the numerical predictions and identify a proportional size scaling between beta grain widths and melt pool widths.

Experimental

predictions

grain

support

melt pool


Input: Results further demonstrate that in situ indirect control of solidification microstructure is possible through direct melt pool dimension control.

in situ

solidification microstructure

melt pool dimension


Input: The effects of electron beam manufactured (EBM) process-induced defects on local microstructural failure initiation and propagation in IN 718 have been investigated.

electron beam

defects

microstructural failure

EBM


Input: Predictions for transgranular fracture, based on local cleavage plane stresses, and for intergranular fracture, based on dislocation-grain boundary (GB) interactions and evolving dislocation pileups, were combined with a crystalline dislocation-density plasticity approach to understand the influence of AM process-induced defects, such as porosity, NbC precipitates, and regions of dry powder.

Predictions

transgranular fracture

cleavage plane

fracture

dislocation

defects

boundary

plasticity

AM

as

precipitates

powder


Input: High local stresses along the peripheries of pores caused crack nucleation, and mismatches in deformation behavior between NbC precipitates and the surrounding matrix led to local stress gradients that induced crack nucleation and decohesion at precipitate/matrix interfaces.

pores

stress

nucleation

deformation

nucleation

precipitates

led


Input: Regions of unmelted powder had significant stress accumulations that initiated failure at low nominal strains.

powder

stress

failure


Input: Failure due to high localized stresses near regions of unmelted powder was dominant over precipitate/matrix decohesion and crack nucleation near pore peripheries.

Failure

nucleation

powder

pore


Input: Based on the predictions, the mechanical behavior of AM alloys is governed by local dislocation-density evolution near process-induced defects, which preferentially nucleate material failure.

predictions

evolution

defects

failure

mechanical

AM

alloys

material


Input: Furthermore, interactions between these different defect types can significantly accelerate failure initiation and propagation.

defect

failure


Input: Lattice structures can add value to high-performance components manufactured by laser powder bed fusion due to their high specific strength and stiffness.

Lattice structures

components

laser powder bed fusion

specific strength

stiffness


Input: A further use of lattice structures is in thermo-mechanical applications, where the high surface area of the lattice may aid heat transfer.

lattice structures

thermo-mechanical

lattice

heat transfer

surface area


Input: However, little characterisation of lattices under thermal loading is currently available in the literature.

lattices

thermal loading


Input: In this study, a custom-built test rig was used to characterise the thermal conduction for three triply periodic minimal surface lattice types, namely: gyroid, diamond and Schwarz primitives, with unit cell size and volume fraction being varied.Results show that thermal conductivity is primarily a function of the material properties and volume fraction of the sample.

triply periodic minimal surface

lattice

unit cell

material properties

sample

diamond

volume fraction

volume fraction

thermal conductivity


Input: However, some effects of the geometry, such as surface area to volume ratio, can be used to explain slight differences in the measured conductivity.

geometry

volume

as

be

area

conductivity


Input: The Schwarz primitive unit cell consistently gave the highest conductivity, with diamond and gyroid unit cells being marginally lower.

unit cell

unit cells

conductivity

diamond


Input: Larger cell sizes typically gave higher conductivity than smaller cells, which can be attributed to greater intra-cell convective heat transfer and better interface coupling with the testing apparatus.The experimental results are used to derive equations that allow samples with a specified thermal conductivity to be designed, thus demonstrating how a component may be manufactured with a custom thermal profile by varying the volume fraction of the lattice.

cell sizes

conductivity

thermal conductivity

cells

be

be

be

heat transfer

interface

experimental

samples

thermal profile

lattice

testing

component

volume fraction


Input: Sensing and closed-loop control are critical attributes of a robust 3D printing process, such as Directed Energy Deposition (DED), in which it is necessary to manage geometry, material properties, and residual stress and distortion.

Sensing

closed-loop control

3D printing

DED

as

Deposition

geometry

material properties

distortion

residual stress


Input: The present research demonstrates multiple modes of closed-loop melt pool size control in laser-wire based DED, a form of large-scale metal additive manufacturing.

research

melt pool

DED

metal additive manufacturing


Input: First, real-time closed-loop melt pool size control through laser power modulation was demonstrated for intralayer control of bead geometry.

melt pool

laser power

bead geometry


Input: Next, an interlayer trend in laser power during the printing of layered components was documented, which inspired the development of novel modes of control.

trend

laser power

components


Input: A controller that modulates print speed and deposition rate on a per-layer basis was developed and demonstrated, enabling the control of either average melt pool size alone or average laser power in coordination with real-time melt pool size control.

controller

print

deposition rate

power

average

average

melt pool


Input: This work demonstrates that accumulated heat in components under construction can be exploited to maintain process stability as print speed and deposition rate are automatically increased under closed-loop control.

heat

process

components

closed-loop control

construction

be

as

deposition rate


Input: This has major implications for overall production efficiency.

production


Input: Control modes are characterized in terms of their effect on local bead geometry, global part geometry, and interlayer effect on energy density, among other factors.

bead geometry

geometry

energy density


Input: Quality control in metal additive manufacturing prioritizes the development of advanced inspection schemes to characterize the defect evolution during processing and post-processing.

Quality control

defect

post-processing

metal additive manufacturing

inspection


Input: This involves grand challenges in detecting internal defects and analyzing large and complex defect datasets in macroscopic samples.

defects

defect

macroscopic


Input: Here, we present an inspection pipeline that integrates (i) fast, micro X-ray computed tomography reconstruction, (ii) automated 3D morphology analysis, and (iii) machine learning-based big data analysis.

inspection

X-ray computed tomography

reconstruction

data

machine


Input: X-ray computed tomography and automated computer vision result in a holistic defect morphology database for the inspected macroscopic volume, based on which machine learning analysis is employed to reveal quantitative insights into the global evolution of defect characteristics beyond qualitative human observations.

X-ray computed tomography

computer vision

defect

macroscopic

quantitative

evolution

defect

qualitative

database

machine


Input: We demonstrate this pipeline by examining the global-scale pore evolution in post-processing of binder jetting additive manufacturing, from the green state, to the sintered state, and to the hot isostatic pressed state of copper.

pore

evolution

post-processing

binder jetting additive manufacturing

sintered

pressed

copper


Input: The pipeline is shown to be effective at detecting and processing the information associated with a large number (∼105) of pores in macroscopic volumes.

be

pores

macroscopic


Input: By quantifying the evolution of (i) the weight of pore morphology parameters and (ii) the pore number and volume fraction of each categorized group, new understandings are developed regarding the effects of sintering and hot isostatic pressing on pore decomposition, shrinkage, and smoothing during post-processing of binder jetting.

evolution

morphology

shrinkage

post-processing

weight

volume fraction

pore

pore

pore decomposition

sintering

hot isostatic pressing

binder jetting


Input: Pore structures with isotropic stiffness fabricated via selective laser melting.

Pore

isotropic

fabricated

selective laser melting


Input: The structures were based on topology optimization and additive manufacturing.

topology optimization

additive manufacturing


Input: The stiffness was experimentally verified.

stiffness


Input: The stiffness and strength were higher than conventional porous metals.

stiffness

strength

porous metals


Input: Recent additive manufacturing technologies can be used to fabricate porous metals with precise internal pore structures and effective performance.

additive manufacturing

fabricate

be

metals

pore

performance


Input: We use topology optimization to derive an optimal pore structure shape with high stiffness that is verified experimentally.

topology optimization

pore

stiffness


Input: The design maximizes the effective bulk modulus and isotropic stiffness, and the performance is compared with Hashin–Shtrikman (HS) bounds.

design

bulk modulus

isotropic

performance

HS


Input: The optimized structure is fabricated via selective laser melting of maraging steel, which is a high-strength, iron-nickel steel that can not easily be made porous with conventional methods.

structure

fabricated

selective laser melting

maraging steel

steel

be

porous


Input: The optimal porous structure achieved 85% of the performance of the HS upper bound in numerical simulations, and at least 90% of them were realized in compressive testing.

porous

performance

HS

numerical simulations

testing


Input: Finally, the performance is discussed relative to that of other metals.

performance

metals


Input: In metal additive manufacturing, microstructural inhomogeneities, like anisotropic mechanical strength and geometric limitations in directed energy deposition, electron beam melting, or selective laser sintering, have led to the exploration of alternative techniques in recent years.

metal additive manufacturing

directed energy deposition

electron beam melting

selective laser sintering

microstructural

anisotropic

strength

led


Input: Among these techniques, fused filament fabrication is an attractive alternative due to its successes in producing dense parts, approaching traditional manufacturing specifications.

fused filament fabrication

traditional manufacturing

specifications


Input: Despite this success, many challenges remain to produce reliable parts with reproducible properties using FFF, particularly in the thermal treatment for part densification.

properties

FFF

thermal treatment

densification


Input: % Ti-6Al-4V powder to create a printable filament.

Ti-6Al-4V powder

filament


Input: Printed Ti-6Al-4V parts using these filaments were sintered at temperatures ranging from 900 to 1340 °C and evaluated by x-ray diffraction, scanning electron microscopy and optical microscopy.

filaments

sintered

temperatures

x-ray diffraction

scanning electron microscopy

optical microscopy


Input: The sintered samples demonstrated a linear decrease in β-phase from 15 to 11 vol.

sintered

samples


Input: % with increasing temperature, while residual stress and Young’ s modulus increased.

temperature

residual stress

s


Input: Additionally, the density of printed and sintered Ti-6Al-4V parts could be increased up to 91% of the theoretical density of Ti-6Al-4V by increasing the sintering temperature up to 1340 °C.

density

density

sintered

sintering

be

theoretical


Input: Samples that were sintered at 1340 °C showed a higher Young’ s modulus compared to SLM samples, likely due to the increased α-phase in samples sintered at 1340 °C.

Samples

samples

samples

sintered

SLM

s


Input: The microstructures of additively manufactured (AM) metal components have been shown to be heterogeneous and spatially variable when compared to conventionally manufactured counterparts.

microstructures

metal

be

additively manufactured

AM

components

manufactured


Input: Consequently, the mechanical properties of AM-metal parts are expected to vary locally within their volume.

mechanical properties

volume


Input: For AM structural components intended to operate in extreme environments, including high-strain-rate loading scenarios, there is a need to quantify variability of mechanical behavior within the same AM-build domain at quasi-static and dynamic strain-rates as well as the effect of heat treatment on the mechanical properties.

AM

heat treatment

components

variability

domain

quasi-static

dynamic

mechanical properties

mechanical

as

as


Input: The objective of this study is to investigate the effect of loading direction and direct-age hardening heat treatment on quasi-static and dynamic mechanical response within an Inconel 718 volume produced by laser powder bed fusion using manufacturer-recommended processing parameters.

hardening

laser powder bed fusion

quasi-static

dynamic

parameters

Inconel 718


Input: Uniaxial compression tests and a split-Hopkinson pressure bar (SHPB) were used to investigate the quasi-static and dynamic response, respectively, of as-built and heat-treated specimens extracted along the three principal processing directions.

compression tests

pressure

quasi-static

dynamic

extracted

heat-treated


Input: Electron backscatter diffraction measurements were made for representative specimens within the build domain to correlate microstructural features to observed location-specific mechanical deformation.

Electron backscatter diffraction

build

microstructural

deformation

mechanical


Input: Results from both quasi-static and dynamic loading show that the recommended processing parameters yield a homogeneous stress-strain response throughout the material volume in the as-built condition.

quasi-static

dynamic

parameters

homogeneous

material


Input: Deformed specimen geometries showed a systematic and repeatable preferential deformation along the build direction, regardless of condition or loading strain rate when loading was applied in either of the two orthogonal processing directions.

Deformed

geometries

deformation

strain rate

build direction


Input: The deformation dependence is found to be related to the underlying, process-induced crystallographic texture and grain morphology.

deformation

grain

be

texture


Input: Two different honeycomb structures are manufactured with LENS system from Ti-6Al-4V alloy.

honeycomb structures

manufactured

LENS

Ti-6Al-4V alloy


Input: Mechanical properties of the Ti-6Al-4V alloy are determined.

Mechanical properties

Ti-6Al-4V alloy


Input: Procedure for acquiring proper data for the elasto-visco-plastic constitutive model is presented.

data

model


Input: Energy-absorption properties of the honeycomb cellular structures are assessed during experimental and numerical testing.

properties

honeycomb

experimental

cellular structures

testing


Input: The paper presents a methodology investigation of honeycomb cellular structures deformation process in quasi-static compression tests.

methodology

honeycomb

process

quasi-static

cellular structures

compression tests


Input: Two honeycomb topologies with different elementary cells were designed and manufactured from Ti-6Al-4 V alloy powder with the use of Laser Engineered Net Shaping (LENS) system and compressed using a universal strength machine.

honeycomb

manufactured

cells

designed

Ti-6Al-4 V alloy

powder

Laser Engineered Net Shaping

LENS

strength

machine


Input: To simulate the deformation process with LS-Dyna software, the mechanical properties of the material were assessed and correlated.

deformation

software

mechanical properties

correlated

material


Input: An elasto-visco-plastic material model (Mat_Plasticity_With_Damage) was used for predicting the material behavior.

material

material


Input: The results of experimental tests and numerical simulations were compared.

experimental

numerical simulations


Input: A reasonable agreement between deformation, failure and force histories was obtained.

deformation

failure

force


Input: Additionally, both the topologies were compared for their energy absorption capabilities.

topologies

energy absorption


Input: The validated numerical modelling with the adopted constitutive model will be used in the further studies to analyze different cellular structures topologies subjected to dynamic loading.

modelling

model

dynamic

be

cellular structures


Input: A novel technique was developed to control the microstructure evolution in Alloy 718 processed using Electron Beam Melting (EBM).

microstructure evolution

processed

Alloy

Electron Beam Melting

EBM


Input: In situ solution treatment and aging of Alloy 718 was performed by heating the top surface of the build after build completion scanning an electron beam to act as a planar heat source during the cool down process.

In situ

surface

scanning

electron beam

heat source

Alloy

as

heating

build

build

cool down


Input: Results demonstrate that the measured hardness (478 ± 7 HV) of the material processed using in situ heat treatment similar to that of peak-aged Inconel 718.

hardness

material

Inconel 718

in situ

heat treatment


Input: Large solidification grains and cracks formed, which are identified as the likely mechanism leading to failure of tensile tests of the in situ heat treatment material under loading.

solidification grains

mechanism

failure

in situ

as

tensile tests

heat treatment


Input: Despite poor tensile performance, the technique proposed was shown to successively age Alloy 718 (increase precipitate size and hardness) without removing the sample from the process chamber, which can reduce the number of process steps in producing a part.

tensile

hardness

performance

sample

process

process

Alloy

precipitate


Input: Tighter controls on processing temperature during layer melting to lower process temperature and selective heating during in situ heat treatment to reduce over-sintering are proposed as methods for improving the process.

temperature

layer

process

in situ

process

heating

heat treatment

as


Input: Lattice structures with isotropic stiffness fabricated via electron beam melting.

Lattice structures

isotropic

fabricated

electron beam melting


Input: The structures were based on topology optimization and additive manufacturing.

topology optimization

additive manufacturing


Input: The designed isotropic stiffness was experimentally verified.

designed

stiffness


Input: The strength was also isotropic as the same with stiffness.

strength

isotropic

stiffness

as


Input: Electron-beam melting (EBM) exhibits advantages over other metal-additive manufacturing techniques owing to its low residual stress, rapid fabrication speed, and high energy efficiency.

melting

EBM

manufacturing

rapid fabrication

residual stress


Input: However, in EBM, metal powder is preheated and sintered to stabilize the temperature gradient and powder position during melting with a high-power electron beam.

EBM

sintered

melting

metal powder

powder

temperature gradient

electron beam


Input: When making a lattice structure by EBM, a certain size of the powder-removing hole is required to remove the sintered remaining metal powder from the lattice.

lattice structure

EBM

sintered

metal powder

lattice


Input: However, a large powder-removing hole can reduce the lattice mechanical performance.

lattice

performance


Input: We conducted topology optimization to derive an optimal lattice structure shape with high isotropic stiffness assuming fabrication by EBM and minimizing the performance reduction owing to fixed large powder-removing holes.

topology optimization

lattice structure

isotropic

fabrication

EBM

performance


Input: The optimized structure was fabricated via the EBM of a Ti–6Al–4V alloy.

structure

fabricated

EBM

alloy


Input: The optimal lattice structure achieved 83% of the performance of the Hashin–Shtrikman upper bound in numerical simulations, but an approximate 20% stiffness reduction was observed in the experiments.

lattice structure

performance

reduction

numerical simulations

stiffness


Input: Selective laser melting (SLM) is a commonly used powder bed fusion metal additive manufacturing (AM) process.

Selective laser melting

SLM

powder bed fusion

metal additive manufacturing

AM

process


Input: Although SLM is preferred due to its near-net-shape part commitment, the deposition rate of this process is slower compared with alternative metal processes.

SLM

near-net-shape

deposition rate

process

metal


Input: A higher deposition rate of SLM can be obtained by increasing the laser scanning velocity and laser power; however, this results in decreased part quality due to the SLM process’ s physical limits.

deposition rate

laser power

SLM

SLM

be

s

laser

quality

process

limits


Input: This study presents the conditions for a higher deposition rate for various process parameters with defocused beams to eliminate the void defects due to keyholing formed in the melt pool.

deposition rate

process parameters

void defects

melt pool


Input: Single bead experiments were conducted, and the thresholds of the process parameters resulting in voids were identified.

bead

process parameters

voids


Input: A melt pool depth-to-width ratio of 0.85 was found to be a critical value for preventing voids in the process.

melt pool

be

voids

process


Input: The melt pool aspect ratio was related with the process parameters by using the normalized enthalpy and the volumetric energy density.

melt pool

aspect ratio

process parameters

energy density


Input: The threshold values of the normalized enthalpy due to voids were independent from the beam diameters.

voids

beam diameters


Input: Moreover, unstable single bead track thresholds were plotted as a function of the beam diameters.

bead

as

beam diameters


Input: In addition to the experiments, a finite element analysis model was built with calibrated absorptivity and heat source parameters to predict the melt pool geometries for a wide range of process parameters (power = 100–370 W, velocity = 200–2000 mm/s, and beam diameter = 100–260 μm).

finite element analysis

calibrated

heat source

geometries

process parameters

melt pool

range

power

beam diameter


Input: A new laser metal desposition process based on an inside-laser coaxial powder feeding system was successfully applied to manufacture reduced activation steel, which is featured with fine microstructure and excellent mechanical properties.

laser

process

manufacture

microstructure

mechanical properties

powder feeding system

steel


Input: In addition, infrared thermal imaging experiments and Abaqus numerical simulation were conducted to characterize the complex thermal history during the laser metal deposition process.

infrared

imaging

Abaqus

simulation

laser metal deposition


Input: The microstructure and mechanical properties of reduced activation steel were systematically investigated in the as-fabricated and heat-treated samples.

microstructure

mechanical properties

steel

heat-treated


Input: The results indicat that the peak temperature increased and the cooling rate decreased in the melt pool when the additional layers were deposited as a result of a cumulative effect of heat in the fabricated thin wall samples.

temperature

cooling rate

melt pool

as

heat

fabricated

samples