Ehsan Toyserkani - Metal Additive Manufacturing

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METAL ADDITIVE MANUFACTURING
A comprehensive review of additive manufacturing processes for metallic structures Metal Additive Manufacturing
Metal Additive Manufacturing

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The development of this book was motivated by our desire to provide foundational material for a core undergraduate course in Mechanical and Manufacturing Engineering, and we envision its use in graduate courses as well. Universities globally are revising their curriculum to incorporate AM‐related courses. This textbook may provide an introductory platform to be adopted in such courses to promote an appreciation for and grasp of AM among both undergraduate and graduate students. This book may also fill a gap for engineers working outside academia who want to appreciate AM processes by identifying links between traditional core physics and engineering concepts courses and AM. The book provides a step‐by‐step understanding of metal AM and a solid foundation of the topic for readers, who will subsequently be well equipped to explore AM research in greater depth.

For a broad range of readers, this book sheds light on various key metal AM technologies, focusing on basic physics and modeling. This textbook is not a literature survey, nor is it intended for readers with no engineering background. In contrast, it is an introduction to basic physical concepts and phenomena of metal AM processes and their applications. Relevant foundational concepts, such as energy deposition, powder bed fusion, and binder jetting processes, are explained in‐depth and illustrated by case studies throughout the book. Additionally, two emerging processes for metal AM: material extrusion and material jetting, are described. Basic design for AM (DfAM) and quality assurance principles are also covered.

We would like to express our sincere gratitude to several people who helped in the preparation of this book. Special thanks to Francis Dibia, Ali Keshavarzkermani, Zhidong Zhang, Yuze Huang, Mazyar Ansari, Andrew Barlow, Misha Karpinska, Donovan Kwong, and Eniife Elebute, who helped us with some materials and produced some of the figures, as attributed in the book. In addition, we acknowledge all organizations, publishers, authors, and companies that permitted use of their figures, plots, and texts; they have been cited accordingly throughout the book. Last but not least, thanks to our families, who make it all worthwhile.

Like any first edition, this textbook may contain errors and typos. We openly welcome the reader's suggestions to be considered in the second edition of this textbook in which multiple problem sets for each chapter will be introduced.

January 2021

Ehsan Toyserkani, Dyuti Sarker, Osezua Obehi Ibhadode, Farzad Liravi,Paola Russo, Katayoon Taherkhani

Waterloo, Ontario, Canada

Abbreviations

2D Two‐Dimensional
3D Three‐Dimensional
3DQCN Three‐Dimensional Quasi‐Continuous Network
AI Artificial Intelligence
AE Auto‐Encoder
Al Aluminum
AL Absolute Limits
ALE Arbitrary Lagrangian–Eulerian
AM Additive Manufacturing
AMCs Aluminum Matrix Composites
AMF Additive Manufacturing File Format
AMGTA Additive Manufacturer Green Trade Association
ANFIS Adaptive Neuro‐Fuzzy Inference System
ANN Artificial Neural Network
ANOVA Analysis of Variance
ANSI American National Standards Institute
APG Absorptivity Profile Group
ASCII American Standard Code For Information Interchange
ASTM American Society for Testing and Materials
BD Big Data
BESO Bidirectional Evolutionary Structural Optimization
BJ Binder Jetting
BJP Binder Jet Printing
BP Backpropagation
BSE Backscattered Electrons
CAD Computer‐Aided Design
CAE Computer‐Aided Engineering
CAGR Compound Annual Growth Rate
CAM Computer‐Aided Manufacturing
CCD Charged‐coupled device
CCT Continuous Cooling Transformation
CDA Constant Drawing Area
CET Columnar‐to‐Equiaxed Transition
CFD Computational Fluid Dynamics
CL Cathodoluminescence
CMOS Complementary Metal‐Oxide Semiconductor
CNC Computer Numerical Control
CNN Convolutional Neural Network
COLIN Convex Linearization
CS Crack Susceptibility
CT Computed Tomography
μCT micro Computed Tomography
CVD Chemical Vapor Deposition
CW Continuous Wave
DAE Differential‐Algebraic Equation
DBN Deep Belief Network
DC Direct Current
DDA Decreasing Drawing Area
DED Directed Energy Deposition
DEM Discrete/Dynamic Element Model
DfAM Design for AM
DfM Design for Manufacturing
DHA Dust Hazard Analysis
DL Deep Learning
DMLS Direct Metal Laser Sintering
DoD Drop‐on‐Demand
DoG Difference of Gaussian
DXF Drawing Exchange Format
EA Electrical Arc
EAM Embedded‐Atom Method
EB Electron Beam
EBAM Electron Beam Additive Manufacturing
EB‐DED Electron Beam Directed Energy Deposition
EBF3 Electron Beam Freeform Fabrication
EBF 3 Electron Beam Fusion
EBM Electron Beam Melting
EB‐PBF Electron Beam Powder Bed Fusion
EDM Electrical Discharge Machining
EIGA Electrode Induction Melting Inert Gas Atomization
EKF Extended Kafman Filter
ELT Effective Layer Thickness
EMFs Electric and Magnetic Fields
ESO Evolutionary Structural Optimization
FBG Fiber Bragg Gratings
FCC Face Centered Cubic
FCM Finite Cell Method
FDM Fused Deposition Modeling
FE Finite Element
FEA Finite Element Analysis
FEG Field‐Emission Gun
FEM Finite Element Method
FFT Fast Fourier Transformation
FGM Functionally Graded Material
FGSs Functionally Graded Structures
FIS Fuzzy Inference System
FMC Ford Motor Company
FN False Negative
FP False Positive
FS Free Surface
GD Gradient Descent
GM General Motors
GMG Geometrically Modified Group
GP Gaussian Process
HA Hydroxyapatite
HAZ Heat‐Affected Zone
HDR Heating Depth Ratio
HF Highly Filled
HIP Hot Isostatic Pressing
HPM Heaviside Projection Method
ICI Inline Coherent Imaging
IDAM Industrialization and Digitization of Additive Manufacturing
IDT Interdigitated Transducers
IN Inconel
IoT Internet of Things
ISO International Standards Organization
ISO International Standards Organization
KF Kafman Filter
KNN K‐nearest neighbors
LaB 6 Lanthanum Hexaboride
LBM Lattice–Boltzmann Method
LCA Life Cycle Assessment
LCF Low Cycle Fatigue
LDED Laser Directed Energy Deposition
LENS Laser Engineered Net Shaping
LGA Lattice Gas Automata
LM Levenberg–Marquardt
LN Large Negative
LoF Lack of Fusion
LP Large Positive
LPBF Laser Powder Bed Fusion
LPM Laser Power Monitoring
LSF Level Set Functions
LSM Level Set Method
LWIR Long Wave Infrared
MAPE Mean Absolute Prediction Error
MC Metal Carbide
MD Molecular Dynamics
ME Material Extrusion
MG Metallic Glass
MJ Material Jetting
MMA Method of Moving Asymptotes
MMCs Metal Matrix Composites
MME Metal Material Extrusion
MMP Micro‐Machining Process
MMV Moving Morphable Voids
MOV Main Oxidizer Valve
MPC Metal–Polymer Composite
MPE Maximum Permissible Exposure
MPM Melt Pool Monitoring
MS Multi‐Speed
MSDS Material Safety Data Sheet
MSE Mean Squared Error
MTPS Multifunctional Thermal Protection System
Nd Neodymium
NDT Non‐Destructive Testing
NFPA National Fire Protection Association
nHA Nano‐Hydroxyapatite
NHZ Nominal Hazard Zone
Ni Nickle
NIR Near‐Infrared
NIST National Institute of Standards and Technology
NN Neural Network
NS Navier–Stokes
OCM Optimality Criterial Method
OCT Optical Coherence Tomography
OEM Original Equipment Manufacturers
OPD Optical Penetration Depth
OTLs Orthogonal Translational Lattices
PBF Powder Bed Fusion
PCA Principal Component Analysis
PDF Point Distribution Function
PF Powder‐Fed
PI Proportional–Integral
PID Proportional–Integral–Derivative
PMC Polymer Matrix Composite
PMZ Partially Melted Zone
PPE Personal Protective Equipment
PPHT Post‐Processing Heat Treatment
PREP Plasma Rotate Electrode Process
PSD Particle Size Distribution
PTA‐DED Plasma Transferred Arc Directed Energy Deposition
PVD Physical Vapor Deposition
PW Pulsed Wave
PZT Piezoelectric
R&D Research and development
RAMP Rational Approximation of Material Properties
RDM Relative Density Mapping
REP Rotating Electrode Process
RF Radio Frequency
RGB Red‐Green‐Blue
RLS Recursive Least Square
RMSE Root Mean Square Error
RNN Recurrent Neural Networks
ROS Reactive Oxygen Species
RTE Radiation Transfer Equation
SAW Surface Acoustic Wave
SD Signal Dynamics
SDAS Secondary Dendritic Arm Spacing
SE Secondary Electrons
SIMP Solid Isotropic Material with Penalization
SINH Sine Hyperbolic Function
SL Sheet Lamination
SLD Super‐Luminescent Diode
SLD‐OCT Super‐Luminescent Diode—Optical Coherence Tomography
SLM Selective Laser Melting
SLP Sequential Linear Programming
SLR Single‐Lens Reflex
SLS Selective Laser Sintering
SN Small Negative
SOM Self‐Organizing Map
SP Small Positive
SQP Sequential Quadratic Programming
SRAS Spatially Resolved Acoustic Spectroscopy
STF Short‐Term Fluctuations
STL Standard Tessellation Language or StereoLithography
STP Standard for the Product Data
ST‐PCA Spatially Weighted Principal Component Analysis
SVD Singular Value Decomposition
SVM Support Vector Machine
TCP Topological Close‐Packed
TEM Transverse Electromagnetic Modes
TGM Temperature Gradient Mechanism
Ti Titanium
TiC Titanium Carbide
Ti‐HA Titanium‐Hydroxyapatite
TMCs Titanium‐Matrix Composites
TN True Negative
TP True Positive
TPMS Triply Periodic Minimal Surface
TRL Technology Readiness Level
TTT Transformation Time Temperature
VC Vanadium Carbides
VED Volumetric Energy Density
VoF Volume‐of‐Fluid
VTM Virtual Temperature Method
WF Wire‐Fed
WF‐EDED Wire‐Fed Electron Beam Directed Energy Deposition
XRD X‐Ray Diffraction
XRF X‐Ray Fluorescence
YAG Yttrium Aluminum Garnet
YLF Yttrium Lithium Fluoride
YVO4 Yttrium Orthovanadate

Nomenclature

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