Input: Revealed the location-specific flow patterns and quantified the speeds of various types of flow.

flow patterns


Input: Reconstructed three-dimensional flow pattern under both conduction-mode melting and depression-mode melting.

three-dimensional

flow pattern

melting

melting


Input: Experimentally analyzed the prevailing physical processes at different locations in the melt pool.

physical processes

melt pool


Input: Melt flow plays a critical role in laser metal additive manufacturing, yet the melt flow behavior within the melt pool has never been explicitly presented.

Melt flow

melt flow

laser metal additive manufacturing

melt pool


Input: Here, we report in-situ characterization of melt-flow dynamics in every location of the entire melt pool in laser metal additive manufacturing by populous and uniformly dispersed micro-tracers through in-situ high-resolution synchrotron x-ray imaging.

in-situ

melt-flow dynamics

in-situ

melt pool

laser metal additive manufacturing

high-resolution

x-ray imaging


Input: The location-specific flow patterns in different regions of the melt pool are revealed and quantified under both conduction-mode and depression-mode melting.

flow patterns

melt pool

melting


Input: The physical processes at different locations in the melt pool are identified.

physical processes

melt pool


Input: The full-field melt-flow mapping approach reported here opens the way to study the detailed melt-flow dynamics under real additive manufacturing conditions.

melt-flow

melt-flow dynamics

additive manufacturing


Input: The results obtained provide crucial insights into laser additive manufacturing processes and are critical for developing reliable high-fidelity computational models.

laser additive manufacturing

high-fidelity

computational models


Input: High resolution X-ray tomography was used to evaluate the efficiency of Hot Isostatic Pressing.

High resolution

Hot Isostatic Pressing


Input: Full consolidation of large internal cavities filled with unmelted powder was demonstrated.

consolidation

powder


Input: Design of such cavities with unmelted powder could improve production rates by eliminating the need for some fraction of hatch melting in the interior of additively-manufactured structures.

Design

powder

production

melting

fraction


Input: HIP is highly effective at closing most typical porosity distributions.

HIP

porosity

distributions


Input: Exceptions are highly interconnected pores and pores near the surface.

pores

pores

surface


Input: Hot isostatic pressing (HIP) of additively manufactured metals is a widely adopted and effective method to improve the density and microstructure homogeneity within geometrically-complex metal structures fabricated with laser powder bed fusion (LPBF).

Hot isostatic pressing

HIP

additively manufactured

laser powder bed fusion

LPBF

density

microstructure

geometrically-complex

fabricated


Input: The role of pores in the fatigue performance of additively manufactured metal parts is increasingly being recognized as a critical factor and HIP post-processing is now heralded as a method to eliminate pores, especially for high-criticality applications such as in the aerospace industry.

pores

fatigue

critical factor

pores

additively manufactured

HIP

as

as

as

aerospace industry


Input: Despite the widely reported positive influence on fatigue performance and high efficiency of pore closure, examples have been reported in which pores have not been entirely closed or have subsequently re-opened upon heat treatment.

fatigue

pore

pores

heat treatment


Input: A variety of porosity distributions and types of pores may be present in parts produced by LBPF and the effectiveness of pore closure may differ depending on these pore characteristics.

porosity

pores

pore

pore

distributions

effectiveness

be


Input: In this work, X-ray tomography was employed to provide insights into pore closure efficiency by HIP for an intentional and artificially-induced cavity as well as for a range of typical process-induced pores (lack of fusion, keyhole, contour pores, etc.

X-ray tomography

pore

pores

HIP

as

as

range

fusion

contour


Input: ) in coupon samples of Ti6Al4V.

samples


Input: The same samples were imaged non-destructively before and after HIP and aligned carefully for side-by-side viewing.

samples

HIP


Input: High pore closure efficiency is demonstrated for all types of cavities and pores investigated, but near-surface pores of all types are shown to be problematic to varying degrees, in some cases perforating the superficial surface and creating new external notches.

pore

pores

pores

be

perforating

surface

notches


Input: Subsequent heat treatments (annealing after HIP) in some cases resulted in internal pore reopening for previously closed internal pores as well as a new “blistering” effect observed for some near-surface pores, which the authors believe is reported for the first time.

heat treatments

annealing

HIP

pore

pores

pores

as

as


Input: Implications of these results for quality control and HIP processing of LPBF parts are discussed.

quality control

HIP

LPBF


Input: Finally, the utility of using HIP to consolidate intentionally-unmelted powder in order to improve production rates of powder bed fusion has great potential and is preliminarily demonstrated.

HIP

production

powder bed fusion

powder


Input: Direct Energy Deposition (DED) systems are currently used to repair and maintain existing parts in the aerospace and automotive industries.

Direct Energy Deposition

DED

aerospace

automotive industries


Input: This paper discusses an effort to scale up the DED technique in order to Additively Manufacture (AM) molds and dies used in the composite manufacturing industry.

DED

Additively Manufacture

AM

composite manufacturing

molds

dies


Input: The US molds and dies market has been in a rapid decline over the last decade due to outsourcing to non-US entities.

molds

dies

outsourcing


Input: Oak Ridge National Laboratory (ORNL), Wolf Robotics and Lincoln Electric have developed a Metal Big Area Additive Manufacturing (MBAAM) system that uses a high deposition rate and a low-cost wire feedstock material.

Laboratory

Robotics

Metal Big Area Additive Manufacturing

MBAAM

high deposition rate

wire feedstock material


Input: In this work we used the MBAAM system with a mild steel wire, ER70S-6, to fabricate a compression molding mold for composite structures used in automotive and mass-transit applications.

MBAAM

fabricate

compression molding

mild steel

composite structures

automotive

mass-transit


Input: In addition, the mechanical properties of the AM structure were investigated, and it was found that the MBAAM process delivers parts with high planar isotropic behavior.

mechanical properties

AM

MBAAM

isotropic


Input: The paper investigates the microstructure and grain of the printed articles to confirm the roots of the observed planar isotropic properties.

investigates

microstructure

grain

isotropic


Input: The manufactured AM mold was used to fabricate 50 composite parts with no observed mold deformations.

manufactured

deformations

AM mold

mold

fabricate

composite


Input: Wire feed metal additive manufacturing offers advantages, such as large build volumes and high build rates, over powder bed and blown powder techniques, but it has its own disadvantages, i.e., lower feature resolution and bead morphology control issues.

feed

build volumes

additive manufacturing

as

powder

build rates

powder bed

feature

bead morphology


Input: A new wire feed metal additive manufacturing process called Metal Big Area Additive Manufacturing (mBAAM) uses a Gas Metal Arc Weld system on an articulated robot arm to increase build volume and deposition rate in comparison to powder bed techniques.

feed

build volume

deposition rate

additive manufacturing process

Metal Big Area Additive Manufacturing

mBAAM

Gas Metal Arc Weld

powder bed techniques

robot arm


Input: The high deposition rate implies a low-resolution process; therefore, parts designed for mBAAM must incorporate the use of machining to achieve certain features.

high deposition rate

process

designed

mBAAM

machining


Input: This paper presents an introduction to how design rules, such as overhang constraint, large weld bead thickness, and support structure, for mBAAM interact in the context of an excavator arm case study, which was designed using topology optimization.

design rules

weld bead

case study

as

support structure

designed

topology optimization

mBAAM

excavator arm


Input: Interactive database for mechanical properties of metal lattice structures.

database

mechanical properties

metal

lattice structures


Input: Lattice Unit-cell Characterization Interface for Engineering compiles 69 sources.

Lattice

Interface

Engineering


Input: Lattice structure data compiled from analytical, experimental, and finite element.

Lattice structure

data

experimental

finite element


Input: Data compilation includes nearly 1650 experimental and finite element data points.

Data

experimental

finite element data points


Input: Lattice data incorporates 18 different common unit cell topologies.

Lattice data

unit cell topologies


Input: With the ever-increasing resolution of metal additive manufacturing processes, the ability to design and fabricate cellular or lattice structures is readily improving.

resolution

metal additive manufacturing

fabricate

design

lattice structures


Input: While there are few limits to the variety of unit cell topologies that can feasibly be manufactured, there is little known about the effect that the underlying unit cell topology has on lattice structure mechanical performance.

limits

unit cell topologies

unit cell topology

performance

be

lattice structure


Input: Increased knowledge of lattice structure performance based on the unit cell topology can aid in appropriate unit cell selection to achieve desired lattice structure mechanical properties.

lattice structure

lattice structure

unit cell topology

unit cell

properties


Input: The objective in this work is to compile metal additively manufactured lattice structure characterization data found in the literature into Ashby-style plots that can be used to differentiate unit cell topologies and guide unit cell selection.

metal

be

additively manufactured

structure characterization

data

unit cell topologies

unit cell


Input: Data gathered from literature encompasses over 69 papers describing 18 different unit cell topologies.

Data

unit cell topologies


Input: Data on mechanical properties such as the effective modulus, Poisson’ s ratio, yield strength, buckling strength, and plateau strength, of lattice structures from analytical models based on mathematical derivations, finite element analysis, and experimental characterization was gathered and synthesized.

Data

mechanical properties

mathematical

finite element analysis

experimental

as

s

yield strength

buckling strength

strength

lattice structures


Input: In total, nearly 1,650 data points for experimental and finite element analysis were compiled along with a variety of analytical models for 18 different unit cell topologies.

data

experimental

finite element analysis

unit cell topologies


Input: The process of gathering the data from the literature along with the assumptions used to compile the data are discussed.

process

data

data


Input: A graphical user interface and database were developed that allows for comparison of different lattice structure mechanical properties based on their unit cell topology.

interface

properties

unit cell topology

database

lattice structure


Input: The Lattice Unit-cell Characterization Interface for Engineers (LUCIE) provides a simple format to guide engineers, scientists, and others towards understanding the relationships of the unit cell topology and the lattice structure mechanical properties, with the intent of guiding appropriate unit cell selection.

Lattice

Interface

unit cell topology

properties

unit cell

simple

lattice structure


Input: Three cases studies are shown for using LUCIE to differentiate unit cell topologies for improved understanding of experimental and simulation-based results (Case Study 1), to identify unit cell topology options for reducing weight while maintaining yield stress or increasing yield stress without reducing weight (Case Study 2), and for quickly narrowing multiple options to an appropriate unit cell topology (Case Study 3).

unit cell topologies

experimental

Case Study

unit cell topology

Case Study

unit cell topology

Case Study

weight

weight

yield stress

yield stress


Input: Drop-on-demand jetting of metals offers a fully digital manufacturing approach to surpass the limitations of the current generation powder-based additive manufacturing technologies.

Drop-on-demand jetting

digital manufacturing

powder-based additive manufacturing

metals


Input: However, research on this topic has been restricted mainly to near-net shaping of relatively low melting temperature metals.

research

shaping

melting temperature


Input: Here it is proposed a novel approach to jet molten metals at high-temperatures (> 1000 °C) to enable the direct digital additive fabrication of micro- to macro-scale objects.

molten metals

direct digital additive fabrication

micro-


Input: The technique used in our research–“MetalJet”-is discussed by studying the ejection and the deposition of two example metals, tin and silver.

research

ejection

deposition

metals

tin

silver


Input: The applicability of this new technology to additive manufacturing is evaluated through the study of the interface formed between the droplets and the substrate, the inter-droplets bonding, the microstructure and the geometrical fidelity of the printed objects.

technology

interface

droplets

bonding

microstructure

geometrical fidelity

additive manufacturing

substrate


Input: The research shows that the integrity of the samples (in terms of density as well as metallurgy) varies dramatically in the two investigated materials due to the different conditions that are required to melt the interface of the stacked droplets.

research

integrity

samples

materials

melt

interface

droplets

density

as

as


Input: Nevertheless the research shows that by a careful choice of the jetting strategy and sintering treatments 3D structures of various complexity can be formed.

research

3D structures

complexity

jetting

sintering

be


Input: This research paves the way towards the next generation metal additive manufacturing where various printing resolutions and multi-material capabilities could be used to obtain functional components for applications in printed electronics, medicine and the automotive sectors.

research

multi-material

functional components

printed electronics

medicine

metal additive manufacturing

be

automotive sectors


Input: Metal additive manufacturing (AM) as an emerging manufacturing technique has been gradually accepted to manufacture end-use components.

Metal additive manufacturing

AM

manufacturing

as

manufacture

components


Input: However, one of the most critical issues preventing its broad applications is build failure resulting from residual stress accumulation in manufacturing process.

build failure

residual stress

manufacturing process


Input: The goal of this work is to investigate the feasibility of using topology optimization to design support structure to mitigate residual stress induced build failure.

feasibility

structure

topology optimization

design

residual stress

build failure


Input: To make topology optimization computationally tractable, the inherent strain method is employed to perform fast prediction of residual stress in an AM build.

topology optimization

strain

residual stress

prediction

AM


Input: Graded lattice structure optimization is utilized to design the support structure due to the open-celled and self-supporting nature of periodic lattice structure.

lattice structure

design

support structure

self-supporting

lattice structure

open-celled


Input: The objective for the optimization is to minimize the mass of sacrificial support structure under stress constraint.

optimization

support structure

stress


Input: By limiting the maximum stress under the yield strength, cracking resulting from residual stress can be prevented.

stress

yield strength

residual stress

cracking

be


Input: To show the feasibility of the proposed method, the support structure of a double-cantilever beam and a hip implant is designed, respectively.

feasibility

support structure

designed

double-cantilever beam

hip implant


Input: The support structure after optimization can achieve a weight reduction of approximately 60%.

support structure

optimization

reduction

weight


Input: The components with optimized support structures no longer suffer from stress-induced cracking after the designs are realized by AM, which proves the effectiveness of the proposed method.

components

support structures

designs

stress-induced cracking

effectiveness

AM


Input: Additive friction stir deposition (AFSD) is an emerging solid-state metal additive manufacturing technology renowned for strong interface adhesion and isotropic mechanical properties.

Additive

deposition

solid-state

interface

properties

metal additive manufacturing

adhesion

isotropic


Input: This is postulated to result from the material flow phenomena near the interface, but experimental corroboration has remained absent.

material

interface

experimental


Input: Here, we seek to understand the interface formed in AFSD via morphological and microstructural investigation, wherein the non-planar interfacial morphology is characterized on the track-scale (centimeter scale) using X-ray computed tomography and the material deformation history is explored by microstructure mapping at the interfacial regions.

interface

microstructural

morphology

deformation

microstructure

X-ray computed tomography

material


Input: X-ray computed tomography reveals unique 3D features at the interface with significant macroscopic material mixing.

X-ray computed tomography

interface

macroscopic

mixing


Input: In the out-of-plane direction, the deposited material inserts below the initial substrate surface in the feed-rod zone, while the substrate surface surges upwards in the tool protrusion-affected zone.

material

substrate

substrate

inserts

tool


Input: Complex 3D structures like fins and serrations form on the advancing side, leading to structural interlocking; on the retreating side, the interface manifests as a smooth sloped surface.

3D structures

interface

surface

as


Input: Microstructure mapping reveals a uniform thermomechanical history for the deposited material, which develops a homogeneous, almost fully recrystallized microstructure.

Microstructure

thermomechanical

homogeneous

microstructure

material

recrystallized


Input: The substrate surface develops partially recrystallized microstructures that are location-dependent; more intra-granular orientation gradients are found in the regions further away from the centerline of the deposition track.

substrate

microstructures

recrystallized

orientation

deposition


Input: From these observations, we discuss the mechanisms for interfacial material flow and interface morphology formation during AFSD.

material

interface


Input: Embedded electronics and sensors are becoming increasingly important for the development of Industry 4.0.

Embedded electronics

Industry 4.0

sensors


Input: For small components, space constraints lead to full 3D integration requirements that are only achievable through Additive Manufacturing.

components

lead

3D integration

Additive Manufacturing


Input: Manufacturing metal components usually require high temperatures incompatible with electronics but Ultrasonic Additive Manufacturing (UAM) can produce components with mechanical properties close to bulk, but with the integration of internal embedded electronics, sensors or optics.

Manufacturing

Ultrasonic Additive Manufacturing

UAM

components

components

sensors

temperatures

electronics

mechanical properties

embedded electronics

optics


Input: This paper describes a novel manufacturing route for embedding electronics with 3D via connectors in an aluminium matrix.

manufacturing

electronics

aluminium matrix


Input: Metal foils with printed conductors and insulators were prepared separately from the UAM process thereby separating the electronics preparation from the part consolidation.

Metal

conductors

insulators

UAM

process

electronics

part consolidation


Input: A dual material polymer layer exhibited the best electrically insulating properties, while providing mechanical protection of printed conductive tracks stable up to 100 °C.

material

layer

electrically

properties

mechanical

printed conductive


Input: General design and UAM process recommendations are given for 3D embedded electronics in a metal matrix.

design

UAM

process

electronics

metal matrix


Input: Functionally graded metals fabricated using high-temperature additive manufacturing can form intermetallics that fracture during printing due to thermal stresses generated by the heat source.

Functionally graded metals

intermetallics

fabricated

fracture

heat source

additive manufacturing

thermal stresses


Input: To address this problem, we introduce a new class of non-equilibrium phase diagrams, termed Scheil Ternary Projection (STeP) diagrams, for designing optimal composition gradients that avoid brittle phases.

non-equilibrium phase diagrams

Scheil Ternary Projection

STeP

composition gradients

brittle


Input: Using the Fe-Cr-Al ternary as a model system, we compare the phase fields in equilibrium and STeP diagrams to show that intermetallic phase fields are dramatically expanded under the rapid solidification conditions in melt-based additive manufacturing, an important effect that must be accounted for when designing composition gradients.

Fe-Cr-Al

as

intermetallic

be

model

phase

equilibrium

STeP diagrams

composition gradients

rapid solidification

additive manufacturing


Input: We present the results of 3D modeling of the laser and electron beam powder bed fusion process at the mesoscale with an in-house developed advanced multiphysical numerical tool.

electron beam

mesoscale

laser

bed fusion

tool


Input: The hydrodynamics and thermal conductivity core of the tool is based on the lattice Boltzmann method.

thermal conductivity

core

tool

lattice


Input: The numerical tool takes into account the random distributions of powder particles by size in a layer and the propagation of the laser (electron beam) with a full ray tracing (Monte Carlo) model that includes multiple reflections, phase transitions, thermal conductivity, and detailed liquid dynamics of the molten metal, influenced by evaporation of the metal and the recoil pressure.

tool

distributions

electron beam

model

phase

evaporation

pressure

powder particles

molten metal

metal

layer

laser

thermal conductivity


Input: We numerically demonstrate a strong dependence of the net energy absorption of the incoming heat source beam by the powder bed and melt pool on the beam power.

energy absorption

heat source

beam

powder bed

beam

melt pool


Input: We show the ability of our model to predict the measurable properties of a single track on a bare substrate as well as on a powder layer.

model

properties

substrate

as

as

powder

layer


Input: We obtain good agreement with experimental data for the depth, width and shape of a track for a number of materials and a wide range of energy source parameters.

experimental data

materials

parameters

range

source


Input: We further apply our model to the simulation of the entire layer formation and demonstrate the strong dependence of the resulting layer morphology on the hatch spacing.

model

simulation

layer

layer

hatch spacing


Input: The presented model could be very helpful for optimizing the additive process without carrying out a large number of experiments in a common trial-and-error method, developing process parameters for new materials, and assessing novel modalities of powder bed fusion additive manufacturing.

model

trial-and-error

process parameters

materials

be

additive

powder bed fusion additive manufacturing


Input: The particle size and shape distributions of metal powders used in additive manufacturing powder bed fusion processes are of technological importance for the final built product.

particle

distributions

metal powders

additive manufacturing

bed fusion


Input: Current three-dimensional (3D) measurements of these distributions assume a spherical shape, while techniques that measure both size and shape are always two-dimensional (2D) measurements of particle projections.

three-dimensional

distributions

spherical

two-dimensional

particle projections


Input: This paper describes a set of techniques using X-ray computed tomography, combined with various mathematical algorithms, to measure the 3D size, shape, and internal porosity of individual particles.

set

X-ray computed tomography

mathematical algorithms

particles

porosity


Input: Calibrated by a limited amount of visual examination of 3D images of individual particles, these techniques can classify powder particles as single near-spherical (SnS) particles, and non-spherical (NS) particles, which consist of either single highly non-spherical particles or multi-particles, where two or more smaller particles have been joined together.

Calibrated

3D images

particles

SnS

particles

non-spherical

particles

non-spherical

multi-particles

particles

visual examination

powder particles

as

NS


Input: From this 3D data, other algorithms can generate 2D particle size and shape information to compare with the results of 2D measurement techniques.

3D data

algorithms

2D particle

2D measurement techniques


Input: These techniques are applied to two metal powders composed of a specific alloy of titanium with aluminum and vanadium, denoted as Ti64, which is in common use as a powder for selective laser or electron beam melting powder bed additive manufacturing.

metal powders

alloy

titanium

aluminum

vanadium

as

as

powder

selective laser

electron beam melting

additive manufacturing

bed


Input: One powder was made with a gas-atomization process, the other with a plasma-atomization process, both have been recycled, and both pass the specifications for additive manufacturing use.

powder

gas-atomization process

plasma-atomization process

recycled

specifications

additive manufacturing


Input: The powders differ in the fraction of NS particles and porous particles, in their size and shape distributions, and in average shape and size statistics.

powders

NS

fraction

particles

distributions

average

statistics

porous


Input: The SnS/NS classification enables one to show how these classes contribute to the overall particle size distributions, even for a single powder type, and is useful for comparing different sources of powder as well as studying how the size/shape distributions of a powder might change over multiple recycling events.

classification

particle size distributions

distributions

recycling

powder

powder

as

as

powder


Input: Electrochemical microstructuring enables the production of polymer-metal hybrids by means of Material Extrusion without the need of coatings.

Electrochemical

production

Material Extrusion

polymer-metal hybrids

coatings


Input: The contact temperature between the metal sheet and the deposited polymer significantly influences the resulting component behavior.

contact

metal

polymer

component


Input: A consolidation roll improves the filling of microstructures for low contact temperatures.

consolidation

microstructures

contact


Input: The development towards higher individualization and functional density pushes the need towards a flexible production of multi-material and lightweight components.

density

flexible production

multi-material

lightweight

components


Input: In this paper, extrusion based additive manufacturing was used to produce polymer-metal hybrids with polypropylene and aluminum alloy.

extrusion

additive manufacturing

polymer-metal hybrids

polypropylene

aluminum alloy


Input: For this purpose, a screw-driven extruder on a six-axis robot was used.

screw-driven extruder

six-axis robot


Input: Due to the adhesion incompatibility of polypropylene and untreated metals, the surface of the aluminum sheets was electrochemically micro-structured.

adhesion

polypropylene

metals

aluminum sheets

surface

electrochemically


Input: The investigations show that this enables a mechanically stressable joint through the filling of the surface microstructures with polymer.

stressable

joint

surface

microstructures

polymer


Input: Investigations on lap shear joints reveal a distinct influence of the contact temperature between the polymer and metal onto the lap shear strength.

lap shear joints

contact

polymer

metal

lap shear strength


Input: A sufficient contact temperature is required for filling surface microstructures.

contact

surface

microstructures


Input: Thus, increased metal and extrusion temperatures favor higher strengths.

metal

extrusion

strengths


Input: Furthermore, the use of a consolidation roll shows beneficial influences in lower temperature ranges due to the application of higher pressures during the polymer strand deposition.

consolidation

pressures

deposition

temperature ranges

polymer


Input: A virtual binocular vision sensor is developed to monitor molten pool width.

virtual binocular

sensor

monitor

molten pool width


Input: A closed-loop controller is designed for molten pool width control.

closed-loop controller

designed

molten pool width


Input: Comparison tests between open and closed-loop control are carried out.

closed-loop control


Input: Gas metal arc (GMA) additive manufacturing (AM) is one of the significant wire and arc AM processes with the ability to produce large-scale metal parts in a layer by layer fashion.

Gas metal arc

GMA

additive manufacturing

AM

wire and arc AM

processes

layer by layer

fashion

metal


Input: Despite this fact, techniques to realize process sensing and geometry control have not been perfectly developed.

process

geometry


Input: This study aims at molten pool width control in GMA AM using a passive vision sensing technique.

molten pool width

GMA AM

passive vision sensing


Input: A virtual binocular vision sensing system consisting of a biprism and a camera is designed to monitor the molten pool geometry.

virtual binocular vision sensing

biprism

camera

designed

monitor

molten pool geometry


Input: The molten pool width in a captured image pair is extracted by a series of procedures, such as sensor calibration, image pair rectification, disparity calculation, and width reconstruction.

molten pool width

image

extracted

calibration

image

reconstruction

as


Input: A verification test is conducted and reveals that the detection error of the sensing system is less than 3%.

verification test

sensing system

error


Input: To keep consistent layer width in each layer, the deviation of the molten pool width is compensated by designing a fuzzy intelligent controller to adjust the arc current in real time.

layer

layer

molten pool width

fuzzy intelligent controller

arc current


Input: The effectiveness of the controller is evaluated via the deposition of thin-walled parts.

effectiveness

deposition

controller

thin-walled parts


Input: The results indicate that the consistency of the molten pool width in GMA AM can be improved when employing the fuzzy controller.

consistency

molten pool width

GMA AM

be

fuzzy controller


Input: Porosity in additively manufactured metals can reduce material strength and is generally undesirable.

Porosity

material strength

additively manufactured


Input: Although studies have shown relationships between process parameters and porosity, monitoring strategies for defect detection and pore formation are still needed.

process parameters

monitoring strategies

defect

porosity

pore


Input: In this paper, instantaneous anomalous conditions are detected in-situ via pyrometry during laser powder bed fusion additive manufacturing and correlated with voids observed using post-build micro-computed tomography.

instantaneous anomalous

in-situ

correlated

voids

pyrometry

micro-computed tomography

laser powder bed fusion additive manufacturing


Input: Large two-color pyrometry data sets were used to estimate instantaneous temperatures, melt pool orientations and aspect ratios.

pyrometry

data

temperatures

melt pool

aspect ratios


Input: Machine learning algorithms were then applied to processed pyrometry data to detect outlier images and conditions.

Machine learning algorithms

processed

data

images


Input: It is shown that melt pool outliers are good predictors of voids observed post-build.

melt pool

voids


Input: With this approach, real time process monitoring can be incorporated into systems to detect defect and void formation.

process monitoring

defect

void

be


Input: Alternatively, using the methodology presented here, pyrometry data can be post processed for porosity assessment.

methodology

data

processed

pyrometry

be

porosity


Input: This paper proposes an additive manufacturing method that combines fused filament fabrication (FFF) 3D printing and an electroforming technology to fabricate multi-material structures composed of resin and metal.

additive manufacturing

fused filament fabrication

FFF

3D printing

electroforming

fabricate

resin

metal


Input: In this method, an FFF 3D printer prints a resin mold that functions as a structural unit in a multi-material structure and as a sacrificial plastic mold for the addition of the metal material.

FFF 3D printer

mold

sacrificial plastic mold

resin

as

as

metal material

structural unit

multi-material structure


Input: This sacrificial mold is eventually removed.

mold


Input: Electroforming the interior of a printed resin mold enables the fabrication of multi-material structures using resin and metal materials.

Electroforming

fabrication

printed resin

mold

multi-material structures

resin

metal materials


Input: The fabrication conditions for multi-material structures when using the proposed method were investigated and the surfaces of the resulting structures were evaluated.

fabrication

multi-material structures

surfaces


Input: The fabrication conditions for the specified thickness per process and the total thicknesses from all the processes were determined.

fabrication

specified thickness

process

processes


Input: Furthermore, our results indicated that the shape of the side of the metal portion depended on the forming precision of the FFF 3D printer.

metal

forming

FFF 3D printer


Input: We present an example of the fabrication of a gear shape from resin and metal.

fabrication

gear

resin

metal


Input: X-ray CT and image analysis enable full surface characterization of LPBF channels.

X-ray CT

surface characterization

image analysis

LPBF


Input: Novel methodology enables roughness profile extraction from 3D deviation data.

methodology

3D deviation data

roughness

profile


Input: 360° roughness characterization enables predictive models for LPBF channels.

roughness

predictive models

LPBF


Input: The increasingly complex shapes and geometries being produced using additive manufacturing necessitate new characterization techniques that can address the corresponding challenges.

complex shapes

geometries

additive manufacturing


Input: Standard techniques for roughness and texture measurements are inept at characterizing the internal surfaces in freeform geometries.

Standard

surfaces

freeform geometries

roughness

texture


Input: Hence, this work presents a new methodology for extracting and quantitatively characterizing the roughness on internal surfaces.

methodology

extracting

quantitatively

surfaces

roughness


Input: The methodology links X-ray CT with complete roughness characterization of channels manufactured by laser powder bed fusion through a novel image analysis approach of X-ray CT data.

methodology

manufactured

image analysis

data

X-ray CT

X-ray CT

roughness

laser powder bed fusion


Input: Global and local orientation parameters are defined to enable a full 360° description of the roughness inside additively manufactured channels.

local orientation

roughness

additively manufactured


Input: X-ray CT data is analyzed to generate 3D deviation data–based on which multiple local roughness profiles are extracted and analyzed in accordance with the ISO 4287:1997 standard.

X-ray CT

data

3D deviation data

extracted

standard

roughness

profiles

ISO


Input: To demonstrate the proposed methodology, seven circular 17-4 PH stainless steel channels produced at different inclinations and with a diameter of 2 mm are investigated as a case study.

methodology

diameter

case study

17-4 PH stainless steel

as

inclinations

mm


Input: Qualitative and quantitative characterization of the roughness is obtained through the use of the proposed methodology.

Qualitative

quantitative

methodology

roughness


Input: A strong dependence of the local roughness on the corresponding α and β orientations is found.

roughness

orientations


Input: A simple regression model is subsequently extracted from the calculated roughness values and allows prediction of Ra-values in the channels for the ranges between 0° ≤ α ≤ 90° and 80° ≤ β ≤ 280°.

simple regression model

extracted

prediction

Ra-values

roughness values


Input: In addition to decreasing the effective hydraulic diameter of a cooling channel, the surface roughness also influences the local Nusselt number, which is quantified using the extracted regression model.

hydraulic diameter

local Nusselt number

extracted

model

cooling channel

surface roughness


Input: This paper reports on the results of a round robin test conducted by ten X-ray micro computed tomography (micro-CT) laboratories with the same three selected titanium alloy (Ti6Al4V) laser powder bed fusion (L-PBF) test parts.

round robin test

X-ray micro computed tomography

micro-CT

laboratories

titanium alloy

laser powder bed fusion

L-PBF


Input: These parts were a 10-mm cube, a 60-mm long and 40-mm high complex-shaped bracket, and a 15-mm diameter rod.

cube

complex-shaped

diameter

bracket


Input: Previously developed protocols for micro-CT analysis of these parts were provided to all participants, including suggested scanning parameters and image analysis steps.

protocols

scanning parameters

image analysis

micro-CT analysis


Input: No further information on the samples were provided, and they were selected from a variety of parts from a previous different type of round robin study where various L-PBF laboratories provided identical parts for micro-CT analysis at one laboratory.

samples

laboratories

laboratory

round robin

micro-CT analysis

L-PBF


Input: In this new micro-CT round robin test which involves various micro-CT laboratories, parts from the previous work were selected such that each part had a different characteristic flaw type, and all laboratories involved in the study analyzed the same set of parts.

micro-CT round robin test

micro-CT

laboratories

flaw

laboratories

set


Input: The 10-mm cube contained subsurface pores just under its top surface (relative to build direction), and all participants could positively identify this.

cube

surface

pores

build direction


Input: The complex bracket had contour pores around its outer vertical sides, and was warped with two arms deflected towards one another.

bracket

contour

vertical


Input: The 15-mm diameter rod had a layered stop/start flaw, which was also positively identified by all participants.

diameter

flaw


Input: Differences were found among participants for quantitative evaluations, ranging from no quantitative measurement made, to under and overestimation of the values in all analyses attempted.

quantitative

overestimation

quantitative measurement


Input: This round robin provides the opportunity to highlight typical causes of errors in micro-CT scanning and image analysis as applied to additively manufactured parts.

round robin

micro-CT scanning

errors

image analysis

as

additively manufactured


Input: Some workflow variations, sources of error and ways to increase the reproducibility of such analysis workflows are discussed.

workflow variations

error

reproducibility

workflows


Input: The ultimate aim of this work is to advance the efficient use of micro-CT facilities for process optimization and quality inspections for additively manufactured products.

micro-CT

inspections

process optimization

quality

additively manufactured products


Input: The results provide confidence in the use of laboratory micro-CT but also indicate the need for further development of standards, protocols and image analysis workflows for quantitative assessment, especially for direct and quantitative comparisons between different laboratories.

laboratory

standards

protocols

image analysis

quantitative

laboratories

quantitative assessment


Input: Very limited Additive Manufacturing (AM) processes have been developed for production of Metal Matrix Composites (MMCs) reinforced by ceramic.

Additive Manufacturing

AM

production

processes

reinforced

Metal Matrix Composites

MMCs

ceramic


Input: Most of these processes use different mixing techniques to mix metal and ceramic powder particles in order to be used in an existing AM process such as Selective Laser Melting (SLM) process.

processes

mixing

process

metal

ceramic powder particles

be

as

AM process

SLM

Laser


Input: The current AM techniques for MMCs fabrication have limitations due to material mixing and the AM process limitations itself.

AM techniques

fabrication

AM process

MMCs

material


Input: This paper introduces a novel AM method for fabrication of MMCs by Thermal Decomposition of Salts (TDS).

AM

fabrication

Thermal Decomposition

MMCs

Salts

TDS


Input: In this method inorganic salts are printed on metal powder bed to fabricate green part.

inorganic salts

metal powder

bed

fabricate


Input: The green part undergoes bulk sintering.

green part

bulk sintering


Input: During bulk sintering the printed inorganic salts are decomposed to fine ceramic particles to form MMC.

bulk sintering

inorganic salts

fine ceramic

MMC


Input: This process is capable of generating MMC structures with uniformly distributed and dispersed ultra-fine ceramic particles in the metal matrix with less limitations and lower cost compared to other existing AM techniques.

process

metal matrix

MMC

ceramic

AM techniques


Input: In this paper, bronze-alumina MMC was fabricated and studied by the TDS process to validate the proposed process.

bronze-alumina

fabricated

TDS process

process


Input: It was also shown that the TDS process can be used to fabricate other types of MMCs besides bronze-alumina due to the nature of the process.

TDS process

process

be

MMCs

bronze-alumina

fabricate


Input: Design of Experiments methodology was used to study and model the effects of sintering parameters on the properties of the bronze-alumina fabricated by the TDS process.

Design of Experiments

model

parameters

properties

TDS process

sintering

bronze-alumina


Input: Due to MMCs unique properties combined with AM benefits, this novel method will be of great interest to various industries such as aerospace applications.

MMCs

be

as

properties

AM

industries

aerospace


Input: Additive manufacturing (AM) promises rapid development cycles and fabrication of ready-to-use, geometrically-complex parts.

Additive manufacturing

AM

fabrication

ready-to-use

geometrically-complex


Input: The metallic parts produced by AM often contain highly non-equilibrium microstructures, e.g.

metallic parts

AM

microstructures


Input: chemical microsegregation and residual dislocation networks.

microsegregation

residual dislocation


Input: While such microstructures can enhance some material properties, they are often undesirable.

microstructures

material properties


Input: Many AM parts are thus heat-treated after fabrication, a process that significantly slows production.

AM parts

heat-treated

fabrication

production

process


Input: This study investigated if electropulsing, the process of sending high-current-density electrical pulses through a metallic part, could be used to modify the microstructures of AM 316 L stainless steel (SS) and AlSi10Mg parts fabricated by selective laser melting (SLM) more rapidly than thermal annealing.

electropulsing

process

high-current-density

electrical pulses

fabricated

metallic part

be

microstructures

stainless steel

SS

AM

selective laser melting

SLM

thermal annealing


Input: Electropulsing has shown promise as a rapid postprocessing method for materials fabricated using conventional methods, e.g.

Electropulsing

postprocessing

materials fabricated

as


Input: casting and rolling, but has never been applied to AM materials.

casting

rolling

AM materials


Input: For both the materials used in this study, as-fabricated SLM parts contained significant chemical heterogeneity, either chemical microsegregation (316 L SS) or a cellular interdendritic phase (AlSi10Mg).

materials

chemical heterogeneity

microsegregation

cellular interdendritic

SLM

316 L SS


Input: In both cases, annealing times on the order of hours at high homologous temperatures are necessary for homogenization.

annealing

homogenization

homologous temperatures


Input: Using electropulsing, chemical microsegregation was eliminated in 316 L SS samples after 10, 16 ms electrical pulses.

electropulsing

microsegregation

electrical pulses

316 L SS


Input: In AlSi10Mg parts, electropulsing produced spheroidized Si-rich particles after as few as 15, 16 ms electrical pulses with a corresponding increase in ductility.

as

as

electropulsing

particles

electrical pulses

spheroidized

ductility


Input: This study demonstrated that electropulsing can be used to modify the microstructures of AM metals.

electropulsing

be

microstructures

AM metals


Input: Architected structural metamaterials, also known as lattice, truss, or acoustic materials, provide opportunities to produce tailored effective properties that are not achievable in bulk monolithic materials.

metamaterials

as

acoustic materials

monolithic materials

truss

properties


Input: These topologies are typically designed under the assumption of uniform, isotropic base material properties taken from reference databases and without consideration for sub-optimal as-printed properties or off-nominal dimensional heterogeneities.

topologies

material properties

properties

heterogeneities

designed

isotropic

databases


Input: However, manufacturing imperfections such as surface roughness are present throughout the lattices and their constituent struts create significant variability in mechanical properties and part performance.

manufacturing imperfections

lattices

variability

mechanical properties

performance

as

roughness

struts


Input: This study utilized a customized tensile bar with a gauge section consisting of five parallel struts loaded in a stretch (tensile) orientation to examine the impact of manufacturing heterogeneities on quasi-static deformation of the struts, with a focus on ultimate tensile strength and ductility.

tensile bar

gauge section

struts

struts

tensile

ultimate tensile strength

ductility

orientation

impact

heterogeneities

quasi-static deformation

manufacturing


Input: The customized tensile specimen was designed to prevent damage during handling, despite the sub-millimeter thickness of each strut, and to enable efficient, high-throughput mechanical testing.

tensile specimen

strut

designed

damage

mechanical testing


Input: The strut tensile specimens and reference monolithic tensile bars were manufactured using a direct metal laser sintering (also known as laser powder bed fusion or selective laser melting) process in a precipitation hardened stainless steel alloy, 17-4PH, with minimum feature sizes ranging from 0.5-0.82 mm, comparable to minimum allowable dimensions for the process.

strut

monolithic

manufactured

process

process

direct metal laser sintering

powder bed fusion

selective laser melting

precipitation hardened

mm

as

steel alloy

minimum feature sizes

dimensions


Input: Over 70 tensile stress-strain tests were performed revealing that the effective mechanical properties of the struts were highly stochastic, considerably inferior to the properties of larger as-printed reference tensile bars, and well below the minimum allowable values for the alloy.

tensile stress-strain tests

mechanical properties

stochastic

properties

struts

tensile bars

alloy


Input: Pre- and post-test non-destructive analyses revealed that the primary source of the reduced properties and increased variability was attributable to heterogeneous surface topography with stress-concentrating contours and commensurate reduction in effective load-bearing area.

non-destructive analyses

topography

primary source

properties

variability

heterogeneous

stress-concentrating

reduction

contours

load-bearing area


Input: This study investigates the feasibility of achieving high deposition rate using wire + arc additive manufacturing in stainless steel to reduce lead time and cost of manufacturing.

investigates

feasibility

cost of manufacturing

high deposition rate

lead time

wire + arc additive manufacturing

stainless steel


Input: The pulse MIG welding technique with a tandem torch was used for depositing martensitic stainless steel 17-4 pH.

MIG welding

tandem torch

martensitic stainless steel

pH


Input: The mechanical and metallurgical properties of the manufactured component were analysed to evaluate the limitations and the extent to which the rate of deposition reaches a maximum without any failure or defect being evident in the manufactured component.

mechanical

metallurgical

manufactured

rate of deposition

failure

defect

manufactured

component

component


Input: Deposition rate of 9.5 kg/h was achieved.

Deposition rate


Input: The hardness was matched for the as deposited condition.

hardness

as


Input: Thermal conductivities of metal powders for additive manufacturing were measured.

Thermal conductivities

metal powders

additive manufacturing


Input: Infiltrating gas pressure and composition influence the powder thermal conductivity.

Infiltrating gas

composition

powder

conductivity


Input: He infiltration yields 200% higher thermal conductivity than Ar or N2 at 1 atm.

infiltration

thermal conductivity

Ar

atm


Input: Powder thermal conductivities depend weakly on temperature from 295 K to 470 K. Gas-enhanced thermal conductivity is consistent with an effective medium model.

Powder

K

temperature

thermal conductivity

model


Input: The thermal conductivities of five metal powders for powder bed additive manufacturing (Inconel 718, 17-4 stainless steel, Inconel 625, Ti-6Al-4V, and 316L stainless steel) were measured using the transient hot wire method.

thermal conductivities

metal powders

Inconel 718

17-4 stainless steel

Inconel 625

316L stainless steel

powder bed additive manufacturing

transient

hot wire method


Input: These measurements were conducted with three infiltrating gases (argon, nitrogen, and helium) within a temperature range of 295–470 K and a gas pressure range of 1.4–101 kPa.

infiltrating gases

gas

argon

nitrogen

helium

K

temperature range

range


Input: The measurements of thermal conductivity indicate that the pressure and the composition of the gas have a significant influence on the effective thermal conductivity of the powder, but that the metal powder properties and temperature do not.

thermal conductivity

pressure

composition

gas

effective thermal conductivity

temperature

powder

metal powder


Input: Our measurements improve the accuracy upon which laser parameters can be optimized in order to improve thermal control of powder beds in selective laser melting processes, especially in overhanging and cellular geometries where heat dissipation by the powder is critical.

accuracy

laser

be

powder

thermal control

geometries

heat dissipation

powder beds

selective laser melting processes


Input: A fundamental understanding of spatial and temporal thermal distributions is crucial for predicting solidification and solid-state microstructural development in parts made by additive manufacturing.

thermal distributions

solidification

solid-state microstructural

additive manufacturing


Input: While sophisticated numerical techniques that are based on finite element or finite volume methods are useful for gaining insight into these phenomena at the length scale of the melt pool (100–500 μm), they are ill-suited for predicting engineering trends over full part cross-sections (> 10 × 10 cm) or many layers over long process times (> many days) due to the necessity of fully resolving the heat source characteristics.

numerical techniques

finite element

finite volume methods

cross-sections

process times

heat source

length scale

melt pool

engineering


Input: On the other hand, it is extremely difficult to resolve the highly dynamic nature of the process using purely in-situ characterization techniques [1].

dynamic

process

in-situ


Input: This paper proposes a pragmatic alternative based on a semi-analytical approach to predicting the transient heat conduction during powder bed metal additive manufacturing processes.

semi-analytical approach

transient heat conduction

powder bed metal additive manufacturing processes


Input: The model calculations were theoretically verified for selective laser melting of AlSi10Mg and electron beam melting of IN718 powders for simple cross-sectional geometries and the transient results are compared to steady state predictions from the Rosenthal equation.

model

cross-sectional geometries

transient

steady state

predictions

Rosenthal equation

selective laser melting

electron beam melting

simple


Input: It is shown that the transient effects of the scan strategy create significant variations in the melt pool geometry and solid-liquid interface velocity, especially as the thermal diffusivity of the material decreases and the pre-heat of the process increases.

transient

variations

geometry

solid-liquid interface velocity

thermal diffusivity

pre-heat

process

melt pool

as

material


Input: With positive verification of the strategy, the model was then experimentally validated to simulate two point-melt scan strategies during electron beam melting of IN718, one intended to produce a columnar and one an equiaxed grain structure.

verification

model

experimentally validated

point-melt

equiaxed grain

electron beam melting


Input: Through comparison of the solidification conditions (i.e.

solidification


Input: transient and spatial variations of thermal gradient and liquid-solid interface velocity) predicted by the model to phenomenological CET theory, the model accurately predicted the experimental grain structures.

transient

liquid-solid interface

predicted

model

phenomenological

CET theory

model accurately

experimental

spatial variations

thermal gradient


Input: Existing commercial three-dimensional (3D) printing systems based on powder bed fusion approach can normally only print a single material in each component.

three-dimensional

powder bed fusion

print

material

component


Input: In this paper, functionally gradient materials (FGM) with composition variation from a copper alloy to a soda-lime glass were manufactured using a proprietary nozzle-based multi-material selective laser melting (MMSLM) system.

functionally gradient materials

copper alloy

soda-lime glass

FGM

multi-material selective laser melting

MMSLM

composition

manufactured


Input: An in situ powder mixing system was designed to mix both metal and glass powders at selective ratios and the mixed powders were dispensed with an ultrasonic vibration powder feeding system with multiple nozzles.

in situ

mixing

designed

metal

glass

powders

ultrasonic vibration powder feeding system

nozzles


Input: From the cross section analysis of the gradient structures, glass proportion increased gradually from the metallic matrix composite (MMC), transition phase to ceramic matrix composite (CMC).

cross section

gradient structures

transition phase

glass

metallic matrix composite

MMC

ceramic matrix composite

CMC


Input: The pure copper alloy joined the MMC part and the pure glass phase penetrated into the CMC part during laser processing, which anchored the glass phase, as the main mechanism of combining pure metal and pure glass by FGM in 3D printed parts.

copper alloy

MMC

glass

CMC

glass

as

pure metal

glass

laser processing

mechanism

FGM

3D printed parts


Input: From results of indentation, tensile and shear tests on the gradient material samples, it showed that mechanical properties of the FGM gradually changed from ductility (metal side) to brittle (glass side).

indentation

mechanical properties

tensile

ductility

brittle

shear tests

material

metal

glass

FGM


Input: The weakest part of the FGM structure occurred at the interface between transition phase and the CMC, which was also the interface between the ductile and brittle phases.

FGM

interface

transition phase

interface

CMC

ductile

brittle


Input: The additive manufacturing (AM) process metal powder bed fusion (PBF) can quickly produce complex parts with mechanical properties comparable to that of wrought materials.

additive manufacturing

AM

metal powder bed fusion

PBF

process

mechanical properties

wrought materials


Input: However, thermal stress accumulated during Metal PBF may induce part distortion and even cause failure of the entire process.

thermal stress

Metal

distortion

failure

process


Input: This manuscript is the second part of two companion manuscripts that collectively present a part-scale simulation method for fast prediction of thermal distortion in Metal PBF.

manuscript

manuscripts

prediction

thermal distortion

simulation

Metal


Input: The first part provides a fast prediction of the temperature history in the part via a thermal circuit network (TCN) model.

prediction

thermal circuit network

TCN

model

temperature


Input: This second part uses the temperature history from the TCN to inform a model of thermal distortion using a quasi-static thermo-mechanical model (QTM).

temperature

TCN

model

thermal distortion

quasi-static thermo-mechanical model

QTM


Input: The QTM model distinguished two periods of Metal PBF, the thermal loading period and the stress relaxation period.

QTM model

thermal loading

stress relaxation

Metal


Input: In the thermal loading period, the layer-by-layer build cycles of Metal PBF are simulated, and the thermal stress accumulated in the build process is predicted.

thermal loading

layer-by-layer

predicted

build cycles

build

Metal

thermal stress


Input: In the stress relaxation period, the removal of parts from the substrate is simulated, and the off-substrate part distortion and residual stress are predicted.

stress relaxation

distortion

predicted

substrate

residual stress


Input: Validation of part distortion predicted by the QTM model against both experiment and data in literature showed a relative error less than 20%.

Validation

distortion

QTM model

experiment

data

relative error


Input: This QTM, together with the TCN, offers a framework for rapid, part-scale simulations of Metal PBF that can be used to optimize the build process and parameters.

QTM

TCN

framework

parameters

simulations

Metal

be

build


Input: Additive manufacturing (AM) processes are subject to lower stability compared to their traditional counterparts.

Additive manufacturing

AM

processes

stability


Input: The process inconsistency leads to anomalies in the build, which hinders AM’ s broader adoption to critical structural component manufacturing.

process

anomalies

structural component

build

AM

manufacturing

s


Input: Therefore, it is crucial to detect any process change/anomaly in a timely and accurate manner for potential corrective operations.

process change/anomaly

accurate


Input: Real-time thermal image streams captured from AM processes are regarded as most informative signatures of the process stability.

thermal image

AM processes

as

process


Input: Existing state-of-the-art studies on thermal image streams focus merely on in situ sensing, feature extraction, and their relationship with process setup parameters and material properties.

state-of-the-art

in situ

process

parameters

material properties

thermal image

feature extraction


Input: The objective of this paper is to develop a statistical process control (SPC) approach to detect process changes as soon as it occurs based on predefined distribution of the monitoring statistics.

statistical process control

SPC

process

distribution

statistics

as

as


Input: There are two major challenges: 1) complex spatial interdependence exists in the thermal images and current engineering knowledge is not sufficient to describe all the variability, and 2) the thermal images suffer from a large data volume, a low signal-to-noise ratio, and an ill structure with missing data.

spatial interdependence

engineering knowledge

variability

data

structure

data

thermal images

thermal images

signal-to-noise ratio


Input: To tackle these challenges, multilinear principal component analysis (MPCA) approach is used to extract low dimensional features and residuals.

multilinear principal component analysis

MPCA

residuals


Input: Subsequently, an online dual control charting system is proposed by leveraging multivariate T2 and Q control charts to detect changes in extracted low dimensional features and residuals, respectively.

control charting

multivariate

control charts

extracted

residuals


Input: A real-world case study of thin wall fabrication using a Laser Engineered Net Shaping (LENS) process is used to illustrate the effectiveness of the proposed approach, and the accuracy of process anomaly detection is validated based on X-ray computed tomography information collected from the final build offline.

case study

process

effectiveness

process

anomaly

fabrication

Laser Engineered Net Shaping

LENS

accuracy

X-ray computed tomography

build


Input: In order to establish modeling and simulation (M & S) in support of Additive Manufacturing Processes (AMP) control for tailoring functional component performance by design, a methodology is introduced for identifying relevant M & S challenges.

modeling

simulation

M & S

M & S

support

Additive Manufacturing Processes

AMP

functional component

methodology

design


Input: This exercise is meant to spur research addressing the specific issue of tailoring functional component performance by design, as well as AMP-related process optimization more generally.

research

functional component

optimization

design

as

as

AMP-related


Input: A composition abstraction that connects process control with functional performance of the multiscale modeling processes is presented, from both the forward and inverse analysis perspectives.

composition abstraction

process control

performance

multiscale modeling

inverse analysis


Input: A brief ontology is introduced that describes the ordering of dependency and membership of all components of a model, which serves the purpose of isolating potential challenge areas.

ontology

model

isolating

components

areas


Input: Certain features of AMPs that are usually ignored by the community during modeling are a specific focus.

AMPs

modeling


Input: Furthermore, two semantically reduced modeling approaches involving continuum abstractions for the computational domains are presented.

semantically

continuum abstractions

computational domains

modeling


Input: The solutions of the relevant system of coupled partial differential equations are used to demonstrate both the positive and negative implications of a series of assumptions routinely made in M & S of AMPs.

partial differential equations

M & S

AMPs


Input: Finally, a discrete element method model is presented to highlight the challenges introduced by the specific nature of this approach.

discrete element method model


Input: The additive manufacturing (AM) process metal powder bed fusion (PBF) can quickly produce complex parts with mechanical properties comparable to wrought materials.

additive manufacturing

AM

metal powder bed fusion

PBF

process

mechanical properties

wrought materials


Input: However, thermal stress accumulated during PBF induces part distortion, potentially yielding parts out of specification and frequently process failure.

thermal stress

PBF

distortion

process failure

specification


Input: This manuscript is the first of two companion manuscripts that introduce a computationally efficient distortion and stress prediction algorithm that is designed to drastically reduce compute time when integrated in to a process design optimization routine.

manuscript

manuscripts

distortion

prediction algorithm

process design optimization

stress

designed

compute time


Input: In this first manuscript, we introduce a thermal circuit network (TCN) model to estimate the part temperature history during PBF, a major computational bottleneck in PBF simulation.

manuscript

thermal circuit network

TCN

model

bottleneck

PBF simulation

temperature

PBF


Input: In the TCN model, we are modeling conductive heat transfer through both the part and support structure by dividing the part into thermal circuit elements (TCEs), which consists of thermal nodes represented by thermal capacitances that are connected by resistors, and then building the TCN in a layer-by-layer manner to replicate the PBF process.

TCN model

conductive heat transfer

thermal circuit elements

TCEs

thermal capacitances

TCN

layer-by-layer

modeling

support structure

resistors

PBF


Input: In comparison to conventional finite element method (FEM) thermal modeling, the TCN model predicts the temperature history of metal PBF AM parts with more than two orders of magnitude faster computational speed, while sacrificing less than 15% accuracy.

finite element method

FEM

thermal modeling

TCN model

temperature

magnitude

computational speed

metal

AM parts

accuracy


Input: The companion manuscript illustrates how the temperature history is integrated into a thermomechanical model to predict thermal stress and distortion.

manuscript

thermomechanical model

distortion

temperature

thermal stress


Input: Additive manufacturing (AM) is a set of emerging technologies that can produce physical objects with complex geometrical shapes directly from a digital model.

Additive manufacturing

AM

set

technologies

model


Input: However, achieving the full potential of AM is hampered by many challenges, including the lack of predictive models that correlate processing parameters with the properties of the processed part.

AM

predictive models

parameters

properties

processed


Input: We develop a Gaussian process-based predictive model for the learning and prediction of the porosity in metallic parts produced using selective laser melting (SLM–a laser-based AM process).

Gaussian

predictive model

prediction

porosity

metallic parts

selective laser melting

SLM

AM process


Input: More specifically, a spatial Gaussian process regression model is first developed to model part porosity as a function of SLM process parameters.

Gaussian

regression model

model

process parameters

porosity

as

SLM


Input: Next, a Bayesian inference framework is used to estimate the statistical model parameters, and the porosity of the part at any given setting is predicted using the Kriging method.

inference framework

model

predicted

porosity


Input: A case study is conducted to validate this predictive framework through predicting the porosity of 17-4 PH stainless steel manufacturing on a ProX 100 selective laser melting system.

case study

framework

porosity

17-4 PH stainless steel

selective laser melting


Input: This paper presents a concept of solidifying small quantities of metal powders in an additive manner, using localized microwave heating (LMH).

metal powders

additive

microwave

heating


Input: The experimental results show solidification of metal powders in forms of spheres and rods (of ∼2 mm diameter) and extension of these rods by adding batches of powder and consolidating them locally as building blocks by LMH.

experimental

solidification

diameter

metal powders

powder

as

mm


Input: A theoretical model applied for the LMH interaction with metal powders attributes a magnetic heating effect also to powders made of non-magnetic metals, due to eddy currents.

theoretical model

metal powders

powders

metals

heating


Input: The experimental observations and numerical results also suggest that micro-plasma discharges between the powder particles initiate their heating process.

experimental

powder particles

heating


Input: The additive LMH approach presented here is intended to extend microwave sintering capabilities, mainly known in volumetric molds, also to applications in the framework of rapid prototyping, additive manufacturing, and 3D-printing.

additive

microwave sintering

additive manufacturing

molds

framework

rapid prototyping


Input: Oscillating laser-arc hybrid additive manufacturing (O-LHAM) is developed.

additive manufacturing


Input: Surface roughness of O-LHAM reduces to 20% of WAAM via laser-arc synergic effects.

Surface roughness

WAAM


Input: High porosity easily occurs within laser-arc hybrid additive manufacturing (LHAM) can be suppressed via periodical beam oscillation.

porosity

additive manufacturing

be

beam


Input: O-LHAM has better tensile properties because of finer microstructure and lower texture content.

tensile properties

finer microstructure

texture


Input: A novel additive manufacturing approach integrating an oscillating laser beam and a cold metal transfer arc was developed to balance the surface accuracy, deposition efficiency, and mechanical properties of the deposited parts.

additive manufacturing

cold metal transfer

laser beam

arc

deposition

mechanical properties

surface accuracy


Input: The new method was termed as oscillating laser-arc hybrid additive manufacturing (O-LHAM).

as

additive manufacturing


Input: The sample properties of the wire-arc additive manufacturing (WAAM), laser-arc hybrid additive manufacturing (LHAM), and O-LHAM processes were compared.

sample

properties

processes

wire-arc additive manufacturing

WAAM

additive manufacturing


Input: First, both the surface roughness and minimum processing margin of the O-LHAM sample were reduced to 20% of the WAAM sample, because the droplet transfer was stabilized by the laser-arc synergic effects.

surface roughness

sample

sample

droplet

WAAM


Input: Second, the grains were refined, and the {001} < 100 > -cube texture content was decreased to 1.6%, as the oscillation induced a strong stirring effect on the molten pool.

grains

molten pool

texture

as


Input: The nondestructive X-ray test suggested that the visible porosity within the O-LHAM sample was suppressed by beam oscillation when the periodically oscillated laser keyhole could “capture” the bubbles, while the porosity within the LHAM sample reached 24%.

X-ray

porosity

porosity

sample

sample

beam

laser


Input: Due to the microstructure changes and the porosity suppression, the O-LHAM almost eliminated the anisotropy of tensile strength and improved the elongation by up to 34%.

microstructure

porosity

anisotropy

tensile strength

elongation


Input: Despite recent advances in our understanding of the unique mechanical behavior of natural structural materials such as nacre and human bone, traditional manufacturing strategies limit our ability to mimic such nature-inspired structures using existing structural materials and manufacturing processes.

mechanical

materials

limit

materials

as

bone

traditional manufacturing

manufacturing processes

mimic


Input: To this end, we introduce a customizable single-step approach for additively fabricating geometrically-free metallic-based structural composites showing directionally-tailored, location-specific properties.

fabricating

composites

properties


Input: To exemplify this capability, we present a layered metal-ceramic composite not previously reported exhibiting significant directional and site-specific dependence of properties along with crack arrest ability difficult to achieve using traditional manufacturing approaches.

composite

properties

traditional manufacturing


Input: Our results indicate that nature-inspired microstructural designs towards directional properties can be realized in structural components using a novel additive manufacturing approach.

microstructural

properties

structural components

designs

be

additive manufacturing


Input: Additive Layer Manufacturing (ALM) of metals is rapidly changing the landscape of industrial manufacturing.

Additive Layer Manufacturing

ALM

metals

industrial


Input: This paper presents the PALMS process, derived from electrolytic plasma polishing, as a solution to this problem.

process

plasma

solution

as


Input: The viability of the process on a scale compatible with commercial use is demonstrated with a prototype industrial implementation.

process

prototype

industrial


Input: PALMS was applied on AISI 316 stainless steel pieces produced either by ALM or by conventional machining (CM.

stainless steel

ALM

conventional machining


Input: ) Surface states, microstructures and other properties were compared pre- and post-PALMS.

Surface

properties

microstructures


Input: Significant improvements in surface state were observed after a 10 min treatment, with a 5-fold reduction in roughness.

surface

reduction

roughness


Input: ALM surfaces were not affected negatively by PALMS in any way measured, and showed slight improvements in hardness and pore density.

ALM

hardness

pore density


Input: Two PVD coatings (TiN and WCC) were finally applied Post-PALMS, to test the compatibility of the process with further industrially relevant surface treatments.

PVD

surface treatments

coatings

TiN

process


Input: PALMS enables good coating adhesion on ALM pieces, with improved friction and wear properties compared to their CM counterparts.

coating

adhesion

ALM

friction

wear properties


Input: As metal Additive Manufacturing (AM) becomes more widely adopted in the aerospace and orthopedic industries, there is increasing demand to improve part quality and reduce overall cost.

As

Additive Manufacturing

AM

aerospace

industries

quality


Input: The high cost of powder feedstock has raised interest in recovering unmelted powder in the build chamber and its reuse in subsequent builds.

powder feedstock

powder

build chamber

builds


Input: While degradation in powder properties with recovery and reuse can cause degradation in part properties, this topic has received rather limited attention.

degradation

degradation

properties

powder


Input: In this study the properties of Ti6Al4V metal powder are evaluated over 30 build cycles in Electron Beam Melting (EBM) AM.

properties

metal powder

build cycles

Electron Beam Melting

EBM

AM


Input: The morphological, microstructural, mechanical, and chemical changes are evaluated in cross-sectioned powder particles and compared to isolated control samples to understand the mechanisms of degradation.

microstructural

samples

degradation

mechanical

powder particles


Input: Results show that in response to the elevated build chamber temperature, the powder undergoes a sub-beta-transus aging heat treatment with powder reuse.

build chamber

powder

powder

heat treatment


Input: Based on nanoindentation hardness measurements, the particles undergo an increase in near-surface hardness (up to 2 GPa) with respect to the core.

nanoindentation

hardness

hardness

GPa

particles

core


Input: Moreover, tint etching revealed an oxidized surface layers consistent with alpha case formation.

etching

oxidized


Input: The particle hardening appears to result from oxygen diffusion during powder recovery and not work hardening related to the mechanical aspects of that process.

particle

diffusion

process

hardening

work hardening

oxygen

powder

mechanical


Input: These results demonstrate the importance of managing/mitigating oxidation of metal powder feedstock to improve its reusability and increasing its overall lifetime.

oxidation

metal powder

feedstock


Input: Components manufactured via Wire + Arc Additive Manufacturing are usually characterised by large columnar grains.

Components

Wire + Arc Additive Manufacturing

columnar grains


Input: This can be mitigated by introducing in-process cold rolling; in fact, the associated local plastic deformation leads to a reduction of distortion and residual stresses, and to microstructural refinement.

be

cold rolling

local plastic deformation

reduction

distortion

microstructural

residual stresses


Input: In this research, inter-pass rolling was applied with a load of 50 kN to a tantalum linear structure to assess rolling’ s effectiveness in changing the grain structure from columnar to equiaxed, as well as in refining the grain size.

research

structure

effectiveness

grain structure

rolling

rolling

tantalum

s

as

as

grain size


Input: An average grain size of 650 μm has been obtained after five cycles of inter-pass rolling and deposition.

average

deposition

rolling


Input: When the deformed layer was reheated during the subsequent deposition, recrystallisation occurred, leading to the growth of new strain-free equiaxed grains.

deformed

deposition

equiaxed grains


Input: The depth of the refined region has been characterised and correlated to the hardness profile developed after rolling.

correlated

hardness

rolling


Input: Furthermore, a random texture was formed after rolling, which should contribute to obtaining isotropic mechanical properties.

texture

rolling

isotropic

properties


Input: Wire + Arc Additive Manufacture demonstrated the ability to deposit sound refractory metal components and the possibility to improve the microstructure when coupled with cold inter-pass rolling.

Wire + Arc Additive Manufacture

rolling

refractory metal

components

microstructure


Input: An innovative wire and arc additive manufacturing variant based on plastic deformation at high temperatures was developed.

wire and arc additive manufacturing

plastic deformation

temperatures


Input: This new variant is capable of collapsing pores that have been formed during the deposition process.

pores

deposition process


Input: The in-situ hot forging technique refines the grain structure and improve mechanical properties in the deposited layer.

in-situ

grain structure

mechanical properties

forging

deposited layer


Input: In this study, we propose a new variant of wire and arc additive manufacturing (WAAM) based on hot forging.

wire and arc additive manufacturing

WAAM

forging


Input: During WAAM, the material is locally forged immediately after deposition, and in-situ viscoplastic deformation occurs at high temperatures.

WAAM

material

deposition

in-situ

deformation

temperatures


Input: In the subsequent layer deposition, recrystallization of the previous solidification structure occurs that refines the microstructure.

layer

deposition

recrystallization

solidification

microstructure


Input: Because of its similarity with hot forging, this variant was named hot forging wire and arc additive manufacturing (HF-WAAM).

forging

forging

arc additive manufacturing


Input: A customized WAAM torch was developed, manufactured, and tested in the production of samples of AISI316 L stainless steel.

WAAM

production

manufactured

samples

stainless steel


Input: Forging forces of 17 N and 55 N were applied to plastically deform the material.

Forging

forces

N

N

material


Input: The results showed that this new variant refines the solidification microstructure and reduce texture effects, as determined via high energy synchrotron X-ray diffraction experiments, without interrupting the additive manufacturing process.

solidification microstructure

texture

as

synchrotron

diffraction

additive manufacturing process


Input: Mechanical characterization was performed and improvements on both yield strength and ultimate tensile strength were achieved.

Mechanical

yield strength

ultimate tensile strength


Input: Furthermore, it was observed that HF-WAAM significantly affects porosity; pores formed during the process were closed by the hot forging process.

porosity

pores

process

forging


Input: Because deformation occurs at high temperatures, the forces involved are small, and the WAAM equipment does not have specific requirements with respect to stiffness, thereby allowing the incorporation of this new variant into conventional moving equipment such as multi-axis robots or 3-axis table used in WAAM.

deformation

forces

temperatures

WAAM

WAAM

equipment

equipment

robots

stiffness

as


Input: A bimetallic additively-manufactured structure (BAMS) is a type of functionally-graded multi-material structure used for achieving different complementary material properties within the same structure as well as cost optimization.

structure

material properties

structure

optimization

multi-material structure

as

as


Input: Wire + arc additive manufacturing (WAAM) offers the capability to fabricate the BAMS in a simultaneous or sequential way.

Wire + arc additive manufacturing

WAAM

fabricate


Input: To fully utilize the benefits of the BAMS, the interfacial joint should be strong, and each of the constituents should have reasonable mechanical integrity.

joint

be

mechanical integrity


Input: For this, a BAMS of low-carbon steel and austenitic-stainless steel was fabricated using a gas-metal-arc-welding (GMAW) -based WAAM process.

low-carbon steel

steel

fabricated

process

GMAW

WAAM


Input: Then, the BAMS was heat-treated at a range of 800 °C to 1100 °C and 30 min to 2 h. This resulted in 35% and 250% increases in the ultimate tensile strength and elongation, compared to the as-deposited BAMS.

heat-treated

range

ultimate tensile strength

elongation


Input: Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDAx), and the Vickers hardness test were used to characterize the BAMS.

Scanning electron microscopy

SEM

X-ray

spectroscopy

Vickers hardness


Input: The additive manufacturing of metals and ceramics generally uses a concentrated laser heat source to form a local melt pool that moves quickly during the process.

additive manufacturing

metals and ceramics

melt pool

laser heat

process


Input: The material is deposited by fast cooling and progressive solidification.

material

cooling

solidification


Input: In this study, the effects of temperature gradient and progressive solidification on residual stress were analyzed using numerical finite-element models for a single rapidly solidifying bead during the deposition process.

temperature gradient

solidification

residual stress

bead

deposition process


Input: Conceptual two- and three-dimensional finite element models are proposed, considering the solidification effect.

three-dimensional

finite element models

solidification


Input: Based on the numerical results, a reduced-order modeling strategy was proposed to efficiently reproduce the final residual stress state of single-bead deposition processes in additive manufacturing, i.e.

modeling

residual stress

deposition processes

additive manufacturing


Input: sequential solidification.

solidification


Input: Although additive manufacturing technology is available for the direct fabrication of metal parts, the process is still in a juvenile state compared to older metal fabrication methods such as sand casting.

additive manufacturing

fabrication

fabrication

casting

metal

metal

as

process


Input: Therefore, limited standards are available stipulating the use of additively-manufactured parts in critical service conditions such as extreme environments or safety components.

standards

safety

as

components


Input: However, since sand casting is suited for multiple units of parts, the time and resources needed to produce a single part through sand casting is not ideal for a competitive market.

sand casting

sand casting


Input: Although additive manufacturing or “3D printing” has been combined with metal casting in the past through “rapid casting” to fabricate sand molds directly, the sand used is stipulated by the 3D printer.

additive manufacturing

3D printing

casting

casting

fabricate

metal

sand

molds

3D printer


Input: The use of specialized sand may result in changes to infrastructure and large amounts of additional sand required to be stored on location.

sand

sand

be


Input: The main question we sought to answer was if traditional foundry sand or “non-standard” sand could be used within a 3D printing system? We report herein that the although the increase in surface roughness may be tolerable, the use of foundry sand within a 3D printer produces molds with less than optimal results, mainly due to the absence of compaction.

foundry

3D printing

foundry

compaction

sand

be

be

surface roughness

3D printer

molds


Input: Binder bleeding via the liquid binder jetting process also contributes to a loss in dimensional quality.

Binder

liquid binder

jetting

quality


Input: The behavior of high performance super duplex stainless steel (SDSS) during additive manufacturing (AM) has been investigated using a novel arc heat treatment technique.

performance

arc

stainless steel

additive manufacturing

AM


Input: Tungsten inert gas (TIG) arc pulses were applied on a disc shaped sample mounted on a water-cooled chamber to physically simulate AM thermal cycles.

Tungsten inert gas

TIG

AM

arc

sample


Input: SDSS base metal and a duplicated additively manufactured structure (DAMS) were used as initial microstructures.

base metal

as

microstructures

additively manufactured


Input: Samples were melted one, five, or 15 times by arc heat treatment.

Samples

melted

arc


Input: Microstructure characterization and modelling were performed to study the evolution of microstructure and properties with successive AM cycles.

Microstructure

evolution

microstructure

properties

modelling

AM


Input: Microstructural changes were dependent on the number of reheating cycles, cooling rate, and peak temperature.

Microstructural

cooling rate

temperature


Input: In particular, the DAMS austenite morphology and fraction changed after reheating to peak temperatures above 700 °C.

austenite

fraction

temperatures


Input: Nitrides and sigma were observed in the high and low temperature heat affected zones, respectively.

Nitrides

temperature

heat affected zones


Input: Sensitization to corrosion was more pronounced in reheated DAMS than in the base metal.

corrosion

base metal


Input: Hardness was increased more by multiple remelting/reheating than by slow cooling.

Hardness

cooling


Input: It was found that AM thermal cycles significantly affect SDSS properties especially for an initial microstructure similar to that produced by AM.

AM

AM

properties

microstructure


Input: Additive manufacturing is a promising and rapidly rising technology in metal processing.

Additive manufacturing

technology

metal


Input: In laser powder bed fusion (LPBF), the most applied metal additive manufacturing process, the repetitive heating and cooling cycles induce severe strains in the built material, which can have a number of adverse consequences such as deformation, cracking and decreased fatigue life that might lead to severe failure even already during processing.

laser powder bed fusion

LPBF

metal additive manufacturing

heating

cooling

material

as

lead

cracking

failure

fatigue life


Input: It has been reported recently that the application of laser shock peening (LSP) can counteract efficiently the named issues of LPBF through the introduction of beneficial compressive residual stresses in the surface regions mostly affected by tensile stresses from the manufacturing process.

laser

peening

LPBF

manufacturing process

residual stresses

tensile stresses

surface


Input: Here we demonstrate how lattice strains implied by LPBF and LSP can efficiently be characterized through diffraction contrast neutron imaging.

lattice

neutron

LPBF

be

diffraction

imaging


Input: Despite the spatial resolution need with regards to the significant gradients of the stress distribution and the specific microstructure, which prevent the application of more conventional methods, Bragg edge imaging succeeds to provide essential two-dimensionally spatial resolved strain maps in full field single exposure measurements.

resolution

stress distribution

strain

microstructure

exposure

imaging


Input: Two-wire TOP-TIG additive manufacturing of titanium aluminide alloys was proposed.

additive manufacturing

titanium aluminide alloys


Input: The Al wire was fed in TOP-TIG welding mode but the Ti6Al4V wire was fed in conventional TIG welding mode.

Al

welding

TIG welding


Input: The main microstructure of the as-fabricated component is α2/γ lamellae.

microstructure

component

lamellae


Input: The different Al content results in the different content and distribution of the α2 phase and the γ phase.

Al

distribution

phase

phase


Input: 50 at.% Al content provides better mechanical properties.

Al

mechanical properties


Input: Titanium aluminide (TiAl) alloys are promising high-temperature structural materials in the aerospace field.

Titanium aluminide

alloys

materials

aerospace


Input: Additive manufacturing is a desirable process for fabricating TiAl alloys.

Additive manufacturing

fabricating

process

alloys


Input: In the process of wire arc additive manufacturing of TiAl alloys, Al-based and Ti-based wires were used as the feedstocks.

process

wire arc additive manufacturing

alloys

as

feedstocks


Input: However, it is hard to ensure the two different wires melt synchronously under the heat of one single arc, so the desired microstructures with γ (TiAl) phase and α2 (Ti3Al) phase are hard to obtain.

melt

heat

arc

phase

phase

microstructures


Input: A two-wire TOP-TIG-based additive manufacturing process for TiAl alloys was proposed in this paper.

additive manufacturing process

alloys


Input: The Ti6Al4V wire and pure Al wire were used as the feedstocks.

Al

as

feedstocks


Input: The Al wire was fed in TOP-TIG mode behind the molten pool, while the Ti6Al4V wire was fed in conventional TIG mode in front of the molten pool.

Al

molten pool

molten pool

TIG


Input: The two wires melt synchronously in a broad range of parameters.

melt

parameters

range


Input: The compositions of the component can be controlled by adjusting the two-wire feeding speeds.

component

be


Input: The main microstructures of the as-fabricated component contain α2/γ lamellae colonies, equiaxed γ grains, and α2 grains.

microstructures

lamellae

component

grains

grains


Input: In the top and middle regions, when the Al content is 45 at.%, the structures are full α2/γ lamellae; as the Al content increases to 50 at.%, some equiaxed γ distributed at the grain boundaries; the component with 55 at.% Al content exhibits the structures consists of equiaxed γ with snowflake-shaped α2/γ lamellae colonies.

Al

lamellae

as

Al

Al

lamellae

grain boundaries

component


Input: In the bottom region, all components exhibit the coarse equiaxed α2 grains with γ laths.

components

grains


Input: As the Al content increases, the α2 phase decreases, but the γ phase increases, and from the top region to the bottom region, the proportion of the α2 increases by about 52 at.%.

As

Al

phase

phase


Input: As the Al content increases, the hardness decreases.

As

Al

hardness


Input: The component with 50 at.% Al exhibits the highest compressive strength with 1762 MPa and a compressive ratio with 26.1.

component

Al

compressive strength

MPa


Input: Additive manufacturing (AM) enables the fabrication of complex designs that are difficult to create by other means.

Additive manufacturing

AM

fabrication

designs


Input: Metal parts manufactured by laser powder bed fusion (LPBF) can incorporate intricate design features and demonstrate desirable mechanical properties.

Metal

manufactured

mechanical properties

laser powder bed fusion

LPBF

design


Input: The process of iteratively converging on the appropriate build parameters increases the time and cost of creating functional LPBF manufactured parts.

process

build parameters

LPBF


Input: This paper describes a fast, scalable method for part-scale process optimization of arbitrary geometries.

process optimization

geometries


Input: The computational approach uses feature extraction to identify scan vectors in need of parameter adaptation and applies results from simulation-based feed forward control models.

feature extraction

parameter

feed


Input: This method provides a framework to quickly optimize complex parts through the targeted application of models with a range of fidelity and by automating the transfer of optimization strategies to new part designs.

framework

optimization

range

designs


Input: The computational approach and algorithmic framework are described, a software package is implemented, the method is applied to parts with complex features, and parts are printed on a customized open architecture LPBF machine.

framework

software

architecture

machine


Input: CrC-Ni successfully deposited onto an AM stainless steel using cold spray coating.

AM

steel

coating


Input: The CrC-Ni coating reduced equivalent residual stresses in the substrate surface.

coating

residual stresses

substrate


Input: CrC-Ni coating improved the surface quality of an AM produced stainless steel.

coating

surface quality

AM

stainless steel


Input: Crack growth mechanism is changed due to the deposition of the CrC-Ni coating.

Crack growth

deposition

coating


Input: Multiaxial fatigue life of AM stainless steel significantly improved by the CrC-Ni coating.

fatigue life

AM

steel

coating


Input: Integration of metal additive manufacturing (AM) and cold spray (CS) technologies provide an unprecedented opportunity to manufacture coated material systems with complex geometrical features.

metal additive manufacturing

AM

technologies

manufacture

coated

geometrical features


Input: The application of these material systems in functionally critical components requires adequate structural integrity, particularly in the presence of cyclic loading.

material

components

structural integrity

cyclic loading


Input: This work aims to study the multiaxial fatigue (axial-torsional cyclic loading) behavior of a coated material system consists of 15Cr-5Ni PH stainless steel (15-5 PH SS) substrate additively manufactured by direct metal laser sintering with a layer of newly commercialized chromium carbide nickel (CrC-Ni) barrier coating deposited by CS coating.

fatigue

cyclic loading

coated

coating

coating

PH

PH

steel

substrate

chromium carbide

additively manufactured

direct metal laser sintering

layer


Input: The influence of AM and CS-induced residual stresses on fatigue performance of test specimens was thoroughly studied.

AM

residual stresses

fatigue


Input: Additionally, the effect of surface roughness and processes induced defects were considered to explain the crack growth mechanism.

surface roughness

processes

defects

crack growth


Input: Stresses assessed by synchrotron X-ray diffraction indicated a substantial accumulation of the residual stresses, particularly in the outer surface of the as fabricated 15-5 PH SS specimens.

synchrotron

diffraction

residual stresses

surface

PH

as


Input: The state of residual stress was changed notably following the deposition of CrC-Ni coating in the axial, hoop, and radial directions of the fatigue test specimen.

residual stress

deposition

coating

fatigue test


Input: Also, CS deposition of CrC-Ni coating caused significant improvement in the surface quality of the additively manufactured components.

deposition

coating

surface quality

additively manufactured


Input: Fatigue test results indicated that the CS deposition of CrC-Ni substantially enhances the fatigue life of the AM-produced 15-5 PH SS substrate in all loading conditions, particularly in the high cycle fatigue regime.

Fatigue test

deposition

PH

fatigue life

fatigue

substrate


Input: The improvement in the fatigue life of the specimens with coating was associated with the reduced surface equivalent residual stress and improvement in the specimens' surface condition (i.e., reduced surface roughness).

fatigue life

residual stress

surface roughness

coating

surface

surface


Input: In addition, the fractographic analysis of the specimen indicated although the crack tends to initiate in the surface of both as fabricated and cold sprayed specimens, the mechanism of crack growth differs notably following the CS coating.

fractographic analysis

surface

mechanism

crack growth

as

sprayed

coating


Input: While the cracks tend to propagate in the planes parallel or with a small deviation from the build layers of the AM produced specimens, deposition of CrC-Ni coating increased the deviation of crack growth plane from the build layers of the substrate.

build layers

build layers

AM

deposition

crack growth

coating

substrate


Input: Electromagnetic wave based laser-powder particle interactions.

particle


Input: Powder features are associated with additive manufacturing process.

Powder

additive manufacturing process


Input: New heat source model considering powder effects.

heat source

powder


Input: A modified heat-source model based on electromagnetic wave theory was proposed to investigate the interactions between powder particles and a laser beam, considering the spatial distribution of particles inside the beam.

model

laser beam

particles

powder particles

spatial distribution

beam