Input: However, complexity in AM is generally manifested in 3D.

complexity

AM


Input: Hence, a lot of recent research is directed towards the development of tailored 3D TO methods for AM design.

research

AM


Input: As is the case with the 2D variants, these 3D TO practices mainly focus on how to minimize overhang area or support volumes, as these constraints are relatively easy to integrate in the TO process.

As

as

process

overhang area

support


Input: In, intensive discussions and experimental computations were conducted for the support volume constrained 3D TO for AM design.

experimental

support

AM


Input: Level set based Pareto is adopted to control and alter the shape boundary where support structure may be required.

set

Pareto

boundary

support structure

be


Input: It is hard to find a unique optimal solution, as each solution is a compromise between the constraints added.

solution

solution

as


Input: A set of Pareto solutions are provided, as seen in 9.

set

Pareto

as


Input: As stated in, the elimination of support volume may be possible but will hardly work for real 3D TO problems in AM design.

As

be

support

AM


Input: Even though it is hard to totally avoid the use of support structures, researchers in still tried to obtain optimal 3D TO structures without supports for several relative simple demonstration cases.

support structures

supports

simple


Input: To avoid the use of supports this study includes a simplified AM fabrication model, implemented as a layerwise filtering procedure into a topology optimization formulation.

supports

AM

model

as

topology optimization


Input: In this way, unprintable geometries are excluded from the design space, resulting in fully self-supporting optimized designs.

geometries

design space

self-supporting

designs


Input: Similar ideas can be found in where support constraint is applied.

be

support


Input: However, this as a compromise between the structural performance and global volume.

as

structural performance

volume


Input: The author of also understands that it would be hard to avoid the use of support structure, and proposed to optimize the 3D structure with necessary support structure in parallel so as to obtain a better compromise.

be

as

support structure

support structure

3D structure


Input: In this study, two separate density fields were proposed to describe the component and support structure layouts respectively.

density fields

component

support structure


Input: A simple critical overhang angle was imposed into the TO process as a constraint.

simple

overhang angle

process

as


Input: The examples presented in 10 and 11 show that more volume used for supports, which can be seen as waste material, results in more material saved for the main structure.

volume

structure

supports

be

as

material

material


Input: Actually, optimizing the functionality of supports for 3D structures to be printed by metallic AM processes would be a more important goal than optimizing material savings, since the support structures in metallic AM processes have a profound impact on the final printing quality.

supports

3D structures

impact

quality

be

be

material

metallic AM

metallic AM

support structures


Input: For example, the build orientation has a direct impact on the TO process since it determines the TO solution space.

build orientation

impact

process

solution


Input: In, the combined optimization of part topology, support structure and build orientation is investigated.

optimization

topology

support structure

build orientation


Input: The research into these complex interrelationships are limited to 2D simple cases, where the impact of build orientation to TO and support optimization is clear.

research

impact

optimization

build orientation

support


Input: This implies that more work should be done in this direction for real 3D industrial cases.

be


Input: If we take the slicing and toolpath planning as additional considerations into the 3D TO process, the complexity would be increased even further.

slicing

process

complexity

toolpath planning

as

be


Input: Finally, there are researchers working on level set TO methods to include AM material deposition path/toolpath as constraints to control sharp angles, deposition gaps, minimum inner hole size and minimum strut size in the topology formation process.

set

AM material

as

sharp angles

hole size

deposition gaps

strut size

topology

process


Input: If the manufacturability of an AM TO solution could not be guaranteed, any kind of optimal design may bring no application value.

manufacturability

solution

AM

be

design


Input: In, manufacturability of the AM components and the cooling rate are considered as constraints and a shape based TO method is proposed.

manufacturability

AM

cooling rate

as


Input: The manufacturability is checked for each layer.

manufacturability

layer


Input: More recently, a new constraint function of the domain which controls the negative impact of porosity on elastic structures in the framework of shape and topology optimization is defined as a special shape derivative and proposed to embed into a level set TO process for AM lightweight design.

domain

impact

framework

process

porosity

elastic structures

topology optimization

design

as

set

AM


Input: Even these methods can obtain a manufacturable TO layout, the boundaryproblems brought by a density based TO method still pose challenges for AM processes.

manufacturable

layout

density

AM processes


Input: Therefore, level set based methods or boundary decomposition with spline interpolation are usually used to do post-processing of the TO results.

set

boundary decomposition

post-processing

spline interpolation


Input: From the discussion of existing research presented above, there are still a lot of difficulties for the development of tailored TO methods and tools for AM lightweight design.

research

tools

AM

design


Input: The work discussed is all based on a single material showing isotropic properties.

material

isotropic


Input: However, with digital controlled deposition, theoretically AM can print different materials with different gradients for multi-functional structures.

deposition

materials

multi-functional structures

AM

print


Input: For example, jetting-based AM processes can print smart structures with multiple polymers.

AM processes

print

polymers


Input: Hence, TO methods and tools to help designers to allocate different material to different regions with optimal quantities for an expected multi-functional structure become critical.

tools

material

multi-functional structure


Input: In, a multivariate SIMP method is proposed to optimize an application dependent multi-material layout.

multivariate SIMP method

multi-material layout


Input: The inclusion of multiple materials in the topology optimization process has the potential to eliminate the narrow, weak, hinge-like sections that are often present in single-material compliant mechanisms.

inclusion

materials

compliant mechanisms

topology optimization process


Input: The demonstration example is the realization of a 3-phase, multi-material 2D compliant mechanism.

multi-material 2D compliant mechanism


Input: One can foresee that if some work in the future can help realize multi-material topology optimization for 3D metal structures, then the complexity capability of AM can be further explored not only for lightweight design but also for a combined multi-function design.

multi-material

optimization

complexity

lightweight

3D metal structures

design

multi-function design

AM

be


Input: Currently, metallic FDM process with metallurgical solidification as a post-process can theoretically realize the joining of multiple metals.

metallic

as

metals

FDM

joining

metallurgical

post-process


Input: There has been extensive exploration of TO for AM in diverse application examples either via standard TO tools or AM oriented tools.

AM

AM

standard

tools

tools


Input: Reports have presented industrial design cases to show the great potential of TO tools for AM lightweight design.

industrial

design

design

tools

AM


Input: EADS presented a component for Airbus.

component

Airbus


Input: However, there are no details about how to embed the AM constraints in the design process of the example.

AM

design process


Input: In the second example, a minimum AM feature size is embedded into the density based TO process and allows to define arbitrary objective functions for multi-physic fields, which is crucial for gradient-based, and thus all topology optimization.

AM

density

process

topology optimization


Input: An example on the comparison study of designing a heat sink between traditional parametric optimization and AM oriented TO is presented in 15.

heat sink

parametric optimization

AM


Input: Apart from density-based methods or level set methods, evolutionary TO methods were also investigated for AM design.

set

AM


Input: In, a recently developed topology optimization method called Iso-XFEM is used.

topology optimization

Iso-XFEM


Input: This method is capable of generating high resolution topology optimized solutions using isolines/isosurfaces of a structural performance criterion.

high resolution

structural performance


Input: XFEM is similar to the BESO method, but removes or adds materials within elements.

BESO method

materials

elements


Input: However, there is no description how the TO process is tailored for AM.

process

AM


Input: It is not difficult to image that embedding AM constraints into an evolutionary TO process would be more difficult than that of density or level set based methods since the process uses discrete optimization.

image

process

process

AM

be

density

set

discrete optimization


Input: In addition, evolutionary based methods still have more difficulties in selection of stopping criteria or convergence analysis.

convergence analysis


Input: As shown and discussed above, though some commercial tools are ready for use, very little AM constraints are considered.

As

tools

AM


Input: The current TO methods and commercialized tools still stay very close to the traditional TO tools.

tools

tools


Input: In addition, including both academic and industrial examples, those studies commonly lack experimental verification and there is no explicit agreement by the scientific community on their aspect ratio, which sets barriers for comparison and TO performance benchmarking.

industrial

experimental

performance

aspect ratio


Input: Therefore, there is still slot of work to be done for developing standard testing and experimental benchmarking examples.

be

standard

experimental


Input: 4.2 Generative design For the TO methods discussed above, people are trying to develop a fully automatic way to define a unique optimal lightweight structure design.

Generative design

lightweight structure

design


Input: However, it is difficult to converge to the optimal solution, especially when multiple objectives are set.

solution

set


Input: Hence, a compromise should be made to sample the solution space when the theoretical global optimal could not be located.

be

be

sample

solution

theoretical


Input: This introduces another design method for AM, generative design.

design

AM

generative design


Input: GD is a set of methods that apply a generative system, rule-based or algorithm-based, to explore the design space and generate candidate solutions for designers.

GD

set

design space


Input: It is usually practiced for architectural design.

design


Input: In structure design, we usually use the second method, applying evolutionary algorithms to sample and generate design solutions that are close to predefined objectives and criteria.

structure design

design

algorithms

sample


Input: in, it is easy to adapt to evolutionary generative design for AM.

generative design

AM


Input: Based on traditional TO methods, discretized version of the density based SIMP method, commercial software providers announced new functions of generative design for AM in their structure design tools and presented a couple of industrial design cases with numerical results.

density

software

generative design

AM

structure design

design

industrial


Input: For example, 16 gives one design example with a set of filtered candidate solutions.

design

set


Input: Similarly, as TO, GD is not new, but introducing AM constraints in traditional GD is still difficult.

as

GD

GD

AM


Input: To solve this problem, recently, researchers developed a new evolutionary generative design method for AM lightweight design to mimic termite behavior for volume construction.

generative design

AM

design

mimic

volume

construction


Input: The proposed methodology uses multi-agent algorithms that simultaneously design, structurally optimize and appraise the manufacturability of parts produced by additive manufacturing.

methodology

algorithms

manufacturability

design

additive manufacturing


Input: Voxels are used to carry the design rules and manufacturing constraints for reasoning and combination during the geometry evolution process.

Voxels

design rules

manufacturing constraints

geometry evolution


Input: However, this method considers support structures as the only AM constraint and has difficulty to include more.

support structures

as

AM


Input: For generative design for AM, there is still a lot of work to do to include more AM constraints and develop more efficient decision making tools to help designers define optimization criteria and candidate solution ranking schemes.

generative design

AM

AM

tools

optimization

solution


Input: Some commercial tools are now available however.

tools


Input: On the other hand, when doing structure design via generative design methods, the global optimum and computational cost should be given attention.

structure design

generative design

be


Input: Recently, researchers began to combine TO with generative models, e.g., generative adversarial networks, and proposed a new concept, deep generative design, which owns the learning capability from the iteration process and existing design data.

generative models

generative adversarial networks

deep generative design

design

process

data


Input: These concepts hold the potential to better integrate existing AM processing knowledge into the generative design procedure to populate and explore more qualified AM design solutions.

AM

AM

generative design


Input: Certainly, generative design is not only used for topology optimization but also can be applied to form synthesis, lattice and surface structure optimization and trabecular structures as a way to explore more design freedom using AM.

generative design

topology optimization

surface structure

trabecular structures

be

as

lattice

optimization

design freedom

AM


Input: 4.3 Lattice structure filling Directly removing or adding material in the design space to search for the global optimal material topology solution is common to TO and generative design methods and, as stated above, there are many difficulties.

Lattice structure

material

material

as

design space

solution

generative design


Input: As a compromise, generative design can include human knowledge to interactively select the candidate solutions so as to reduce the problem complexity.

As

as

generative design

complexity


Input: Therefore, this is an indirect lightweight design method for AM, which is also called lattice configuration, 18.

lightweight

lattice configuration

design

AM


Input: To obtain lattice structures, generally we have two approaches: 1.

lattice structures


Input: Homogenization and 2.

Homogenization


Input: Density based mapping.

Density


Input: The former homogenizes the lattice structure as representative volume elements, like solid material.

lattice structure

as

elements

material

volume


Input: The lattice structures are similar to the micro porous for the traditional solid structure in homogenized volumes.

lattice structures

porous

homogenized volumes

structure


Input: In this way, special properties should be assigned to the representative volumes and then we can apply traditional TO or other structure optimization methods to operate the special volumes.

properties

structure optimization

be


Input: Representative researches that apply this method can be found in and 19 illustrates the general workflow.

be

workflow


Input: The second approach maps the density values obtained from non-penalized TO results onto the explicit predefined lattice structures with optional adaptation to improve the approximation accuracy of mechanical response.

density

lattice structures

accuracy

mechanical response


Input: Based on this approach, uniform or graded lattice structures can be obtained.

lattice structures

be


Input: Example studies can be found in.

be


Input: 20 shows an example where different predefined lattice structures are used to map the solid volume TO contours.

lattice structures

contours

volume


Input: Although the two appraoches are not hard to understand, the operation and optimization of lattice structures is quite complicated, especially for large size structure design.

optimization

lattice structures

structure design


Input: The first problem is the representation/digitalization of lattice structures.

lattice structures


Input: Usually, solid representation or surface representation can be used for individual lattice units.

surface

be

lattice units


Input: But when filled into solid hulls, the number of lattice units is very big, which makes the CAD file difficult to operate, including sweeping, meshing/mapping and tessellation.

solid hulls

lattice units

tessellation

CAD file


Input: Secondly, when doing numerical simulation, the computation cost is much higher since many more finite element units are required.

numerical simulation

computation

finite element


Input: Thirdly, when filling lattice structures into solid hulls, one needs to use uniform lattice in trimming or non-uniform lattice with conformal interface, which depends on specific design cases.

lattice structures

design

solid hulls

lattice

lattice

interface

trimming


Input: Some researchers stated that conformal lattice structures have better structural performance than that of uniformed.

conformal lattice structures

structural performance


Input: However, the operation of conformal lattice is more complicated and more difficult to control the manufacturability since they are not, like uniform lattices usually are, derived from benchmarking results.

conformal lattice

manufacturability

lattices


Input: After that, the computation cost is a big issue, not only for the representation, but also for simulation and manufacturing.

computation

simulation

manufacturing


Input: That is why some researchers proposed to use kernel or symbolic representations for lattice units.

lattice units


Input: Finally, the most important challenge is how to obtain the global optimum when using lattice structures.

lattice structures


Input: The approximation process further reduces the original design space and introduces more errors.

process

design space

errors


Input: Predefined and benchmarked limited lattice structures with fixed parameters are just a subset of the design variants.

lattice structures

design

parameters


Input: Actually, even for predefined lattice units, there are more parameters that can be modified and adjusted to specific design cases.

lattice units

design

parameters

be


Input: Currently, many optimization studies for lattice structures are only limited to density, represented by strut diameter, and very little work focuses on parameter optimization and computation benchmarking for large lattice structure design cases.

optimization

parameter

optimization

computation

lattice structures

lattice structure design

density

strut diameter


Input: Therefore, to be practical, current methods and tools from academic codes or commercial software tools all adopt knowledge based methods with TO methods for lattice filling.

be

tools

software

lattice filling


Input: Usually, a lattice library is built to store predefined lattice units, benchmarked with numerical simulation or manufacturability analysis, and then a limited set of control options, concerning the lattice unit size, strut diameter, layout orientation, etc., are available for the filling operation.

lattice

manufacturability

layout

lattice units

lattice unit size

numerical simulation

set

strut diameter


Input: This is the main workflow of current tools.

workflow

tools


Input: As said before, although relatively small or medium sized lattice structures can be obtained, one not only sacrifices the stiffness but also it may be more difficult to search for the original global optimal lightweight design solution.

As

be

be

lattice structures

design

stiffness

lightweight


Input: If one only considers the lightweight effect in the design, lattice filling may not be the optimal choice.

lightweight

design

lattice filling

be


Input: However, lattice structures can bring other benefits, e.g.

lattice structures


Input: energy absorption and heat conduction that solid structures may not have.

energy absorption

heat conduction


Input: This would be an important factor to encourage research and practice in the lattice domain.

be

research

lattice domain


Input: 5 Tools and methods for optimizing surface structure As discussed above, the global optimal for structure design is usually hard to obtain.

Tools

surface structure

structure design

As


Input: Similar to lattice structures, which are made artificially, natural porous structures become a set of special elements to deal with specific design requirements.

lattice structures

design

porous

set

elements


Input: Examples include among others lightweight infill, porous scaffolds, energy absorbers, micro-reactors, heat conductors, or self-adaptating structures.

lightweight

infill

porous scaffolds

micro-reactors

heat conductors


Input: These structures/functionalities have been known for some time, but due to the ability of AM to produce these complex structures, they now become part of the solution principles that can be applied by the product designer.

AM

complex structures

solution

be


Input: Hence, the mimicking and post-processing of natural inspired or randomly generated complex topologies become a new design practice, which is called bio-inspired or biomimetic design.

post-processing

topologies

bio-inspired

design

biomimetic design


Input: Its goal is to generate either lightweight structures with unexpected mechanical properties, similar to the lightweight design methods mentioned in the last section, or multi-functional surface structures as addressed here.

lightweight structures

mechanical properties

lightweight

design

surface structures

as


Input: This type of design is more difficult than that of relatively regular or conformal periodic lattice structures.

design

lattice structures


Input: Hence, the design and simulation focuses more on the form and shape of the surfaces while the mechanical properties and AM constraints are hard to consider due to their extreme complexity.

design

simulation

surfaces

mechanical properties

complexity

AM


Input: Generally, two design approaches, direct/indirect reproduction of natural topologies via reverse engineering and generic bio-inspiration using design rules or guidelines, are conducted in this domain.

design

topologies

reverse engineering

bio-inspiration

design rules

domain


Input: Driven by the wide application in the medical domain, scaffolds and implants usually require similar internal surface topologies to the natural structures they are mimicing.

medical

implants

domain

scaffolds

surface topologies


Input: cell spreading, strength distribution.

cell

strength

distribution


Input: The main methods to generate irregular porous structures with complex internal surface topologies are either filling or hollowing materials from an initial design via specific algorithms.

porous

surface topologies

design

materials

algorithms


Input: A representative filling method is Triply Periodic Minimal Surface, which is an implicit surface with intricate structures.

Triply Periodic Minimal Surface

implicit surface


Input: Researchers add different operation algorithms to do the filling with these surface units so as to approximate the original CAD model's skin.

operation algorithms

CAD model

surface

as


Input: For the hollowing process, sub-volumes are generated via a set of specific algorithms within the original 3D CAD model and used to do Boolean operations.

process

algorithms

model

set

Boolean operations


Input: A shape function is applied in to design a pore model and then a subtractive Boolean operation is conducted between the pore and the original solid CAD models to obtain the final scaffold model.

design

pore

pore

model

scaffold model

subtractive

Boolean operation

CAD models


Input: The process is illustrated in 23.

process


Input: Similarly, a Voronoi tessellation method is adopted in to do the material hollowing.

Voronoi tessellation

material hollowing


Input: Apart from the internal surface structure generation, external surface structure design also attracts attention since using AM to print complex shapes for art or customized shapes has become popular.

surface structure

surface structure

design

AM

print

complex shapes

art


Input: In artistic design, T-splines and Voronoi tessellation or predefined pattern bases are commonly used for defining complex surface topologies.

design

T-splines

Voronoi tessellation

surface topologies

pattern


Input: In, a generative design method is applied to populate complex surface topologies via the use of predefined patterns.

generative design

surface topologies


Input: A recursive grammar is set for the generation of solid boundary surface models, suitable for a variety of design domains.

set

boundary

design


Input: Freeform 3D surface topologies can be formed by a set of 2-manifold polygonal sub meshes as shown in 24.

Freeform 3D

topologies

be

as

set


Input: However, the optimization for artistic design is not so obvious.

optimization

design


Input: To develop special surface structures for personalized casts/braces, a new topology optimization method is proposed in.

surface structures

topology optimization


Input: The novel TO method is based on thin plate elements on the two-dimensional manifold surfaces instead of 3D solid elements so as to reduce the computation cost for shape optimization.

elements

as

two-dimensional

computation

optimization

manifold surfaces

3D solid elements


Input: To decrease the threshold of customization of surface structure for the public when using AM, in, an interactive CAD design tool is proposed.

surface structure

AM

CAD

tool


Input: This tool uses predefined reference unit models with the inputs of user's stylings to automatically generate customized hollowed surface topologies for fashion.

tool

surface topologies

fashion


Input: Similar to other existing 3D porous structure design methods, this tool is mainly based on Voronoi tessellation and curve fitting methods.

structure design

Voronoi tessellation

tool


Input: 26 shows the surface topology generation process.

surface topology

process


Input: The main advantage of this tool is that its predefined reference models can be benchmarked and tested to ensure manufacturability, which will avoid problems during AM.

tool

be

manufacturability

AM


Input: Similar to structure topology optimization, surface structure design and optimization face more difficulties in the modelling, simulation and embracing of AM constraints.

structure

optimization

optimization face

surface structure

design

modelling

simulation

AM


Input: This requires more work on the data structure, simulation driven analysis and optimization.

data

optimization

simulation


Input: A lightweight and convenient analysis platform should be developed to efficiently acquire the calculation results for valid surface structure design and optimization.

lightweight

optimization

platform

be

surface structure

design


Input: Currently, there is very little research invesigating the design guidelines of surface structure in AM.

research

design

surface structure

AM


Input: Most of the design pratices are limited at non-metallic AM processes.

design

AM processes


Input: However, there is an ugent need in the medical application domain where special functional surface structures are critical.

medical application

domain

surface structures


Input: 27 presents a dental component where a bio-insipred surface structure with a special treatment function is printed using L-PBF.

dental

component

bio-insipred surface structure

L-PBF


Input: Reverse engineering is used to generate the surface structure.

Reverse engineering

surface structure


Input: However, the modelling and function validation of such surface structure has not yet been studied.

modelling

validation

surface structure


Input: Hence, design methods and modelling tools should be developed to support the medical fabrication application for metal AM processes.

design

modelling

be

support

medical

fabrication

metal AM


Input: 6 Manual optimization of internal part topology One of the enablers within AM is the ability to optimize the internal part topology.

optimization

internal part topology

internal part topology

AM


Input: In the previous sections automated topology optimization procedures for internal and surface part geometry were discussed.

topology optimization

surface

geometry


Input: In many cases these automated methods are not required or applicable and other ways of defining the internal part topology are used.

internal part topology


Input: With subtractive methods, structuring the product internal surfaces is hard or limited to very basic geometric features and production steps.

subtractive

production

surfaces


Input: Many of the commercially successful AM applications relate to internal transport of media through the AM product.

AM

AM

transport


Input: In relation to the additive manufacturing challenges, three subsets of AM features for internal transport of media can be identified; macro channel geometry, mini/micro channels and printed permeability.

additive manufacturing

AM

transport

be

macro channel geometry

mini/micro channels

permeability


Input: For macro channel geometry, down-facing surfaces of the channel may experience stability problems during printing.

macro channel geometry

surfaces

channel

stability


Input: For mini/micro channels, the feature size may be close to the limitations of the printing device which may result in walls failing to print, channels being blocked and cumbersome removal of excess print material.

mini/micro channels

feature size

be

material

print

print


Input: Finally, AM permeable structures are created by ensuring process-induced porosity.

AM permeable structures

porosity


Input: Here the main challenge is finding stable process settings that allow for both the production of permeable and solid structures.

process settings

production

permeable and solid structures


Input: 6.1 Internal geometry at macro level In classical part production, channels for the transportation of viscous media are manufactured using conventional subtractive production methods like drilling, thus resulting in straight channels with round cross section and sharp corners.

Internal geometry

macro level

straight channels

round cross section

classical part production

conventional subtractive production methods

drilling

manufactured


Input: With the use of AM the location and shape of these channels can be optimized.

AM

be


Input: In L-PBF and at macro level, the top surfaces of the round holes have the tendency to sag or collapse, and the cross section of the channel has to be optimized.

L-PBF

macro level

surfaces

cross section

channel

be


Input: Thomas investigated the quality of produced channels and found that round holes up to a diameter of 7mm could be printed with minimal problems.

quality

diameter

be


Input: Above that, sagging of the overhanging surface is noticed, as well as possible curl, leading to recoater collisions.

surface

as

as


Input: Other channel designs have been proposed.

channel


Input: With the use of AM, cooling channels in injection molding inserts can be made conformal to the mold's product surface and located in areas critical to the quality of the die's function.

AM

injection molding

cooling channels

mold

die

be

surface

quality

areas


Input: Conformal cooling channels have been used to reduce cycle time and product warpage.

Conformal cooling channels

product warpage


Input: Kitayama compared the effect of conformal cooling channels and conventional cooling channels for injection molding.

conformal cooling channels

conventional cooling channels

injection molding


Input: Results showed an improvement of the cycle time of 53% and a reduction of product warpage by 46% compared to conventional cooling channels.

reduction

product warpage

conventional cooling channels


Input: Although conformal cooling for IM is widely researched and benefits have been proven, actual application in industry lags behind.

conformal cooling

industry


Input: It is considered beneficial only for complex plastic geometries, that are difficult to cool quickly and uniformly and for very high production volumes.

plastic

geometries

production


Input: H researched using conformal cooling channels in hot metal extrusion and also found significant production efficiency improvements.

conformal cooling channels

hot metal extrusion

production


Input: Current research into manifold design has two main themes; mass reduction and flow optimization.

research

reduction

optimization

design


Input: Conventional methods create straight cooling channels, where connections result in pressure loss, increase the temperature and noise, which influences the reliability and lifetime of the system.

cooling channels

pressure

temperature

reliability


Input: Ma investigated multiple geometry adjustments which can be made when using AM.

geometry

be

AM


Input: AM enables the design of fluent corners, smooth transitions between cooling channel diameters and the removal of unwanted drilling cavities, resulting in decrease in pressure loss by up to a factor of 3.

AM

drilling

design

fluent corners

cooling channel

pressure


Input: 6.2 Mini and Micro internal geometry in AM For mini and micro levels of geometry, used for transport of fluidic media, the minimal feature size of the AM technology chosen is often the limiting factor.

internal geometry

AM

AM technology

micro levels

geometry

transport

feature size


Input: Thomas investigated some of these limits, for example as shown in 31.

limits

as


Input: Printing of free standing walls and pilars is also a limiting factor as both the achievable minimal cross sectional area and maximal aspect ratio are limited.

as

area

aspect ratio


Input: In sectors like heating, ventilation, and air conditioning, automotive, aero and electro-cooling, heat exchangers play a vital role in the energy efficiency.

heating

automotive

electro-cooling

heat exchangers


Input: The heat transfer performance is dependent on the surface area to volume ratio.

heat transfer

volume

surface area


Input: Using mini and micro channels, this ratio can be increased, thus increasing the performance/mass ratio of the heat exchanger.

be

heat exchanger


Input: Arie investigated the performance of Ti64 air-water manifold-microchannel heat exchangers.

performance

heat exchangers


Input: Key to the intended efficiency increase was the production of thin fins with high aspect ratio's.

production

high aspect ratio


Input: Non AM-based production alternatives were considered slow, costly, not able to meet the aspect ratios or not possible to produce in the desired material.

production

aspect ratios

material


Input: Compared to classical designs the manifold micro-channel show respectively 30performance increase in gravimetric heat transfer density.

designs

heat transfer density


Input: It was argued that inaccuracy of the production process reduced the manifold performance as some of the channels were blocked and the ideal fin thickness of 150 could not be realized.

production

process

performance

as

be


Input: Mei put the use of AM to a case study where they produced a highly integrated catalytic burner for auxiliary power units based on PEM-fuel cells.

AM

case study

catalytic burner

auxiliary power units

PEM-fuel cells


Input: This resulted in a volume reduction of 70% from 41L to 11L and a weight reduction of 60% from 30 kg to 12 kg.

volume reduction

reduction

weight


Input: 6.3 Printed permeability Calignano investigated the relation between material and process properties to fabricate both stochastic and non-stochastic porous structures.

permeability

material

process

stochastic

fabricate

non-stochastic porous structures


Input: Parts were created using three different scanning strategies scanning lines, and rotating scanning patterns for each new layer) and by modifying the hatch distance hd.

scanning strategies

scanning

scanning patterns

layer

hatch distance


Input: It was found that hatch distances in excess of 0.20 mm were needed to be able to create distinct walls.

hatch distances

mm

be


Input: Below that, wall formation was hampered by agglomeration of powder particles.

powder particles


Input: The rotating scanning strategy using hd of 0.5 mm resulted in stochastic, foam-like structures, both with open and closed pores and porosity values of 43Collins investigated the use and production of a permeable membrane heatsink produced by AM.

scanning strategy

stochastic

foam-like structures

mm

production

AM

pores

porosity

permeable membrane


Input: In order to find the process settings that will result in permeable walls, test cubes were printed with fins on top with a height of 1 mm and wall thicknesses varying from 150 to 500 The core of the cubes was used to determine bulk porosity.

process settings

mm

wall thicknesses

core

bulk porosity


Input: All fins below 300 failed to print while 300 fins were successfully printed only for process settings resulting in low bulk porosity.

print

process settings

bulk porosity


Input: The 400 and 500 fins printed successfully for all process settings used.

process settings


Input: 7 Functional material complexity The design process can also consider that to solve some technological problems or to optimise some local properties, some processes allow building up multi-material objects or objects with material gradients.

Functional material complexity

design process

properties

processes

multi-material

material gradients


Input: In some cases there has been significant progress although it increases the complexity of simulation and of process planning of AM-based value chains.

complexity

process planning

simulation


Input: In addition, there are no standard functionalities in the commercial software that could support such definitions, which must be managed manually or directly defined on the legacy software associated to specific processes.

standard

software

software

processes

support

be


Input: One basic functionality relates to material gradient of polymers and elastomer parts manufactured with voxel-based technologies.

material gradient

manufactured

technologies

polymers

elastomer


Input: The design process criticaly addresses the local characteristics of the material for each voxel of the object.

design process

voxel

material


Input: Another feature that is mostly used for metallic parts is lattice structure that could help in designing internal structures used to support the parts but also to minimize weight with respect to given functionalities.

feature

lattice structure

metallic parts

internal structures

support

weight


Input: In highly developed sectors for metal fabrication, in particular aeronautic and medical applications, AM processes use many metals like stainless steel, titanium, aluminum, cobalt chrome and nickel alloys.

metal

metals

stainless steel

titanium

aluminum

cobalt chrome

nickel alloys

fabrication

AM processes

medical applications


Input: An important feature of metal is its microstructure.

feature

metal

microstructure


Input: For a given metal, there can be a variety of microstructural features that affect its mechanical properties.

metal

be

microstructural

mechanical properties


Input: The size of grains, micro-segregation of alloying elements, phases within the metal and size of dendrites relates to the tensile strength and ductility.

grains

micro-segregation

alloying elements

metal

dendrites

tensile strength

ductility


Input: During the AM process, the microstructure is formed in-situ and would depend obviously on the process parameters and material used.

AM process

microstructure

in-situ

process parameters

material


Input: The microstructure of metals determines the mechanical properties of the part such as yield strength, ductility and hardness.

microstructure

mechanical properties

metals

as

strength

ductility

hardness


Input: Varying the process parameters like the energy sources and fill patterns can lead to differences in grain structure.

process parameters

grain structure

lead


Input: Such issues are both a very important potential advantage but also an additional complexity when considering the AM design process.

complexity

process

AM


Input: Functionally Graded Materials are defined as a class of advanced materials characterised by spatial variation in material composition across the volume, contributing to corresponding changes in material properties in line with the functional requirements.

Functionally Graded Materials

as

class of advanced materials

material

spatial variation

composition

volume

material properties


Input: The multi-functional status of a component is tailored through the material allocation at microstructure to meet an intended performance requirement.

component

material

microstructure

performance


Input: Microstructural gradation contributes to a smooth transition between properties of the material.

Microstructural

transition

properties

material


Input: Another approach is based on Young's modulus variation for the determination of the mechanical propertiesgradients, and consequently material microstructure or composition variations.

variation

composition

mechanical

material


Input: Another interesting proposition comes from who proposes an interpretation of the material with intermediary density as a lattice cellular structure that could be composed by several materials.

material

as

be

intermediary density

lattice cellular structure

materials


Input: Homogeneous FGM composition creates porosity or density gradients by modulating the spatial microstructure or morphology of lattice structures across the volume of material through a voxel approach.

Homogeneous FGM composition

porosity

density gradients

spatial microstructure

lattice structures

morphology

volume

voxel

material


Input: This method can be called densification FGMThe directionality, magnitude and density concentration of the material substance in a monolithic anisotropic composite structure contributes to functional deviations such as stiffness and elasticity.

be

material

anisotropic composite

as

densification

magnitude

density concentration

monolithic

elasticity


Input: The gradual transition from a solid exterior to a porous core leads to an excellent strength-to-weight ratio.

transition

porous

core


Input: Even if new standards are partly addressing such models, the development of mathematical representations useful for both design and simulation is still in progress.

standards

mathematical

design

simulation


Input: FGM can also address the aspect of multi-materiality through an approach of dynamically composed gradients or complex morphology.

FGM

complex morphology


Input: The geometric and material arrangement of the phases controls the overall functions and properties of the FGM component.

material

properties

FGM

component


Input: Multi-material FGM seeks to improve the interfacial bond between dissimilar or incompatible materials.

Multi-material

materials

FGM

interfacial bond


Input: Distinct boundaries can be removed through a heterogeneous compositional transition from a dispersed to an interconnected second phase structure, graded layers with discrete compositional parameters or smooth concentration gradients.

boundaries

be

heterogeneous

transition

phase

parameters


Input: Once again, material models are too complicated to be used for simulation.

material

be

simulation


Input: Demonstration and validation during the design phase of expected characteristics is still to be expected in a general manner.

validation

design

be


Input: But this is an interesting issue to be expected because, by fusing one material to another three-dimensionally using a dynamic gradient, the printed component can have the optimum properties of both materials.

be

material

fusing

three-dimensionally

dynamic

properties

materials

component


Input: It can be transitional in weight, yet retaining its toughness, wear resistance, impact resistance or its physical, chemical, biochemical or mechanical properties.

be

weight

toughness

wear resistance

impact

mechanical properties


Input: Multi-material FGM can also provide location-specific properties tailored at small sections or strategic locations around pre-determined parts.

Multi-material

properties

FGM


Input: Some AM technologies are providing such opportunities.

AM technologies


Input: Construction of such parts could be of interest to solve design issues in order to avoid multi-part assemblies or complex joints for example.

Construction

be

design


Input: Simulation models are still to be implemented and validated mostly because the design of heterogeneous compositional gradients are very complex.

Simulation

be

design

heterogeneous


Input: They can be divided into four types: a transition between two materials, three materials or above, switched composition between different locations or a combination of density and compositional gradation.

be

transition

materials

materials

composition

density


Input: The key design parameters of FGM include the dimension of the gradient vector, the geometric shape and the repartition of the equipotential surfaces.

design

dimension

geometric shape

FGM

equipotential surfaces


Input: The features and functionality of the component are further determined by the direction of the gradient within the material composition.

component

material

composition


Input: The design and types of the volumetric gradient can be classified according to 1D, 2D and 3D, and distribution of materials uniformly or through special patterns.

design

be

distribution

materials


Input: Defining the optimum material distribution function requires extensive knowledge of material data that includes the chemical composition, its characteristics and the manufacturing constraints.

material

material

distribution

data

chemical composition

manufacturing constraints


Input: At present, there are no design guidelines on material compatibility, mixing range for materials with variable and non-uniform properties and a framework for optimal property distribution such as choice of spatial, gradient distribution and the arrangement of transition phases is also lacking.

design

material

as

mixing

materials

properties

framework

property

distribution

distribution

transition phases


Input: When generating graded components of high to low strength, the changing material properties brought about by modifications to the microstructure have to be carefully measured and quantified.

components

strength

material properties

microstructure

be


Input: Tamas-Williams suggested two useful approaches to model the response of functionally graded components using the exponential law idealisation and material elements Finite Element Method analysis can also be used to show and suggest an optimised set of elements under pre-determined circumstances to provide a better understanding of how the material properties will behave.

model

Finite Element Method analysis

material properties

functionally graded components

material elements

be

elements

set


Input: In order to generalise the use of FGM, it is crucial to understand the resulting differences between the predicted and real components.

FGM

predicted

components


Input: By knowing the required mix of properties, the required arrangement of phases, and compatibility of materials design rules and methods have to be established to avoid undesirable results.

properties

materials

design rules

be


Input: Knowledge of the relationship can be gained through shared databases as a catalogue of material performance information.

be

as

material

databases


Input: Richards first proposed a computational approach of using CPPN encodings and a scalable algorithm using NEAT to embed functional morphologies and macro-properties of physical features using multi-material FGM through voxel-based descriptions by a function of its Cartesian coordinates.

algorithm

morphologies

multi-material

macro-properties

FGM

coordinates


Input: Some progresses are still expected but FGM or multi-material parts in general are being seriously considered as solutions for design evolution of products in the future.

FGM

multi-material

as

design


Input: This is already used for polymers and elastomers and this is in progress for metallic products.

polymers

elastomers

metallic


Input: 8 Assembly and part integration considerations It is well recognized that it is possible to exploit the potential of additive manufacturing at product level.

Assembly

additive manufacturing


Input: As one may infer by the existing standards, AM technologies already play a significant role not only for single parts but also at product level.

As

standards

AM technologies


Input: Therefore, the classical Design for Assembly approaches have to be reconsidered in order to take advantage of these AM opportunities.

Design for Assembly

be

AM


Input: An n-part product may be classified as static, movable, or compliant assembly and it may have components of the same or different materials.

be

as

assembly

components

materials


Input: AM technologies enable the possibility to produce not only a single part of an assembly, but directly the assembled product.

AM technologies

assembly


Input: This review shows many possible joints directly fabricated either using polymers or metals.

fabricated

polymers

metals


Input: Furthermore a deep discussion of polymer-based non-assembly mechanisms may be found in, proving that the polymer-based AM technologies are close to maturity for this kind of application.

be

AM technologies


Input: 35 shows a metallic compliant joint for a snake-like surgical robot, produced by PBF.

metallic compliant joint

robot

PBF


Input: In 36, the detail design of a rotational joint and a snap-fit feature are shown for a nanosatellite metallic cubic structure fabricated by L-PBF.

design

snap-fit feature

cubic structure

joint

metallic

L-PBF


Input: But what about the design rules to fully exploit the AM technologies in assembly manufacturing? In the following, a brief analysis of the design rules and in particular of the part consolidation steps in designing a product will be considered.

design rules

design rules

part consolidation

AM technologies

assembly

be


Input: 8.1 Assembly design rules As deeply discussed in, when dealing with assemblies and AM technologies, one main issue still to be adequately addressed is the geometrical product specification.

Assembly

AM technologies

As

be

specification


Input: In fact, no specific ISO-GPS or ASME-GD & T standard dedicated to AM processes exists, leaving design as a cumbersome process of defining geometrical requirements of assembly features or of single parts using a language dedicated to conventionally manufactured products.

standard

process

manufactured products

AM processes

assembly

design

as


Input: Referring to an assembly with fixed connection type, general rules to design fasteners/connectors, in particular snap-fit features, are presented with respect to polymer-based AM processes in, and to metal-based ones in.

assembly

AM processes

design

snap-fit features


Input: These general rules address issues on fastener/connector shape, wall thickness, gap width, staircase effect on sloped surfaces, and on the influence of anisotropy on the assembly product mechanical behavior.

wall thickness

surfaces

anisotropy

assembly

mechanical


Input: Dealing with non-assembly mechanisms, design rules are discussed mainly referring to polymer-based AM processes like extrusion-based, material jetting, and vat photopolymerization processes.

design rules

processes

AM processes

material jetting

vat photopolymerization


Input: The design rules refer to the minimization and the removal of the supports used during the non-assembly product fabrication, the effect of build orientation on the smoothness of the mechanism, and the selection of the clearance between assembled parts.

design rules

smoothness

mechanism

clearance

supports

fabrication

build orientation


Input: Considering the latter issue, in a benchmark is proposed to assess the lowest clearance limits for non-assembly mechanisms.

benchmark

clearance limits


Input: 8.2 Part consolidation Part consolidation is the first and most relevant step in design for assembly.

Part consolidation

consolidation

step

design for assembly


Input: But this is not the case when exploiting AM processes since they enable non-assembly mechanisms, multi-material printing, and easier functional integration.

AM processes

multi-material printing


Input: A significant example of AM part consolidation is the one reported in.

AM part


Input: The original portable hydraulic manifold was used for in-situ testing of aircraft components, a 17-part assembly, and was completely redesigned as a single-part product, with 60% less weight, the same footprint, a 53% shorter height, and with a more reliable and robust design with respect to the original one, deeply exploiting a metal powder bed fusion technology.

in-situ

aircraft components

assembly

metal powder bed fusion

as

weight

design