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1. Correlation of Process Parameters and Surface Finish of Laser
Sintering Rapid Prototyping Technique
By
Ritesh Sharma
YMCAUST/Ph32/2012
J C Bose University of Science & Technology, YMCA, Faridabad
Faculty of Engineering and Technology
Department of Mechanical Engineering
PhD Thesis Presentation
on
Under the supervision of
Dr Sanjeev Kumar Dr Rajeev Saha
Professor Assistant Professor
2. Outline
Introduction
1
Objective of the Study
2
Materials and Methods
3
Experimentation and Modelling
4
Results
5
Conclusion
6
Future Scope and Limitations
7
References
8 2
3. Introduction
• Prototype
– A prototype can be defined as a model that represents a product
or system.
– Prototyping is essential in the development of products and all
industrial nations have prototyping centers. In fact, prototyping
plays a major role in the advancement of technology.
– In the prototyping development cycle, initial prototypes are
built, tested and reworked as necessary until an acceptable
prototype is finally achieved from which the complete system
or product can be developed.
3
5. Virtual Prototypes
• Computer-based models without the
option of a physical part.
• It provides a virtual 3-D prototype that
can be manipulated from all views and
angles.
• The computer program/software can
then test most of the aspects of the
product such as vibration, thermal and
mechanical stresses, forces, materials
and weight.
5
6. Rapid (Physical) Prototypes
• Produces physical prototypes in short time
(within hours or days rather than weeks).
• These prototypes are frequently used to
quickly test the product's look, dimension,
and feel.
6
7. Rapid Prototyping (RP)
• A family of fabrication processes developed to make engineering
prototypes in minimum lead time based on a CAD model of the
item.
• Traditional method is machining
– Can require significant lead-times – several weeks, depending
on part complexity and difficulty in ordering materials
• RP allows a part to be made in hours or days, given that a computer
model of the part has been generated on a CAD system
7
8. Historical Background
• In 1892 US patent (No. 473901) Blanther proposed a method to
constitute a topographic map by layered manufacturing.
• Matsubara (1974) of Mitsubishi proposed a topographical process with a
photo-hardening photopolymer resin to form thin layers stacked to make
a casting mould. (basis for SLA in 1984)
• There are 274 patents registered in US during 1986-1998 as issued in
Terry Wohler’s annual RPM Report.
• SLS was developed and patented by Ross House-Holder in 1979. But it
was improved and commercialised by Carl Deckard at University of
Texas in Austin in 1980’s.
• SLM started in 1995 at the Fraunhofer ILT in Aachen, Germany. (patent
DE 19649865) 8
9. Why Rapid Prototyping is Important
• Product designers want to have a physical model of a new part
or product design rather than just a computer model or line
drawing
– Creating a prototype is an integral step in design
– A virtual prototype may not be sufficient for the designer to
visualize the part adequately
– Using RP to make the prototype, the designer can see and feel the
part and assess its merits and shortcomings
9
11. Methodology of Rapid Prototyping
1
2 Process Planner
CAD Drawing
Post Processing
Direct
Manufacturing
3
4
11
12. Applications of Rapid Prototyping
• Models to validate the design
in terms of dimensions,
geometry and aesthetics.
• Jewellery design.
Prototypes and Models
• Detailed models for
presentations and
validation
Architecture
• Implants like bones, skull,
Dentistry, hearing aids and
even tissues
• Human models for teaching
aids
Medical Applications
• Duplicates of Objects
• Usually Scaled up or scaled
down
Reverse engineering
Rapid
Prototyping
12
13. Rapid Prototyping to Additive Manufacturing
• The limitation of RP is to create models or prototypes for
visualisation and feel only.
• Rapid Manufacturing and Additive Manufacturing were coined
when machines progressed to manufacture functioning items.
13
14. Additive Manufacturing
• Additive manufacturing is the official industry standard term
(ASTM F2792) for all applications of the technology.
It is defined as the process of joining materials to make
objects from 3D model data, usually layer upon layer, as
opposed to subtractive manufacturing methodologies.
• Synonyms are additive fabrication, additive processes, additive
techniques, additive layer manufacturing, layer manufacturing,
freeform fabrication, desktop manufacturing.
14
15. Difference between Rapid Prototyping and Additive
Manufacturing
• Additive manufacturing encompasses several RP technologies
• Rapid Prototyping is a subset of Additive Manufacturing
15
16. Classification of Additive Manufacturing
● Liquid Based
● Solid Based
● Powder Based
As per Material Used
● VAT Photopolymerisation
● Material Extrusion
● Binder Jetting Process
● Directed Energy Deposition
● Sheet Lamination
● Material Jetting
● Powder Bed Fusion
As per Technology Used
16
18. Category Description Binders Material(s) used Commercial
form
VAT
polymerisation
Liquid photosensitive polymer is
selectively cured/ hardened by
polymerisation
Ultraviolet Rays/
Lasers
Photopolymer Resins, Stereolithography
Material Jetting Drops of the material to be used are
selectively deposited layer by layer
Self-Binders Polymers in drop form, Wax Multi-jet modelling
Binder Jetting A liquid bonding agent is selectively
scanned to join the powder bed.
Resins, glue Powder 3DP
Material
Extrusion
Material is selectively deposited in semi-
liquid form through an orifice.
Self-Binder on
solidification
Polymers: ABS, Nylon, etc. Fused Deposition
Modelling
Powder Bed
Fusion
Laser heat selectively fuses the powder
spread on the bed
Thermal Energy,
Lasers? Electron
Beams
Nylon, Polymers, Stainless Steel,
Aluminium, Cobalt, Steel titanium,
Chrome, copper and their alloys,
composites and ceramics
Selective Laser
Sintering, Selective
Laser Melting
Sheet
Lamination
Sheets of the material are bonded and
then trimmed to the desired shape
Ultrasonic
welding, glue,
synthetic binders
Effectively any sheet material
capable of being rolled. Paper, plastic
and some sheet metals
Laminated object
Manufacturing
Directed Energy
Deposition
Thermal energy is focused selectively to
melt the material and then fuse together
Electron Beam
Melting, Lasers
Only Metals and alloys Laser melted
deposition
18
19. VAT Photo Polymerisation (Stereolithography)
The Vat polymerisation process uses Plastics and
Polymers.
Polymers: UV-curable Photopolymer resin
Resins: Visijet range (3D systems)
Advantages:
• High level of accuracy and good finish
• Relatively quick process
Disadvantages:
• Relatively expensive
• Lengthy post processing time and removal from resin
• Limited material use of photo-resins
• Often requires support structures and post curing for
parts to be strong enough for structural use
19
20. Material Jetting (Drop on Demand (DOD))
The material jetting process uses polymers and
plastics.
Polymers: Polypropylene, HDPE, PS, PMMA,
PC, ABS, HIPS, EDP
Advantages:
• The process benefits from a high accuracy of
deposition of droplets and therefore low waste
• The process allows for multiple material parts
and colours under one process
Disadvantages:
• Support material is often required
• A high accuracy can be achieved but materials
are limited and only polymers and waxes can be
used 20
21. Binder Jetting (3DP)
• Metals: Stainless steel
• Polymers: ABS, PA, PC
• Ceramics: Glass
• All three types of materials can be used
with the binder jetting process.
Advantages:
• Parts can be made with a range of different colours
• Uses a range of materials: metal, polymers and ceramics
• The process is generally faster than others
• Multi-material method
Disadvantages:
• Not always suitable for structural parts, due to the use of binder material
• Additional post processing can add significant time to the overall process 21
22. Material Extrusion (Fuse deposition modelling (FDM))
• The Material Extrusion process uses
polymers and plastics.
• Polymers: ABS, Nylon, PC, PC, AB
Advantages:
• Widespread and inexpensive process
• ABS plastic can be used, which has good
structural properties and is easily accessible
Disadvantages:
• The nozzle radius limits and reduces the final
quality
• Accuracy and speed are low when compared to
other processes and accuracy of the final model
is limited to material nozzle thickness
• Constant pressure of material is required in order
to increase quality of finish
22
23. Sheet Lamination (Laminated Object Manufacturing)
• Effectively any sheet material capable of
being rolled.
• The most commonly used material is
paper.
Advantages:
• Benefits include speed, low cost, ease of material handling
• Cutting can be very fast of the shape outline, not the entire cross sectional area
Disadvantages:
• Finishes can vary depending on paper or plastic material but may require post
processing to achieve desired effect
• Limited material use
• Fusion processes require more research to further advance the process into a more
mainstream positioning 23
24. Direct Energy Deposition (LENS)
• The Laser Melting process uses metals
and not polymers or ceramics
Advantages:
• Ability to control the grain structure to a high degree
• Useful in repair applications,
Disadvantages:
• Slow speed and rough surface finish
• Lack of structural properties in materials
• Size limitations
• High power usage
24
25. Powder Bed Fusion (Laser Sintering/Melting and EBM)
• The Powder bed fusion process uses any
powder based materials, but common
metals and polymers used are:
• Nylon, ABS, Polymers, Stainless Steel,
Titanium, Aluminium, Cobalt Chrome,
Steel
Advantages
• No binder requirement
• No costly post processing
• Near full dense parts
Disadvantages
• Expensive and High Laser power required
• Melt pool instabilities and poor surface finish
25
26. Metal Rapid Prototyping
Metal Rapid
Prototyping
Indirect Metal RP
SLS
SLA
FDM
LOM
Direct Metal RP
Laser Based
Laser Binding
DMLS
SLM
Laser Cladding
LMD
DMD
LENS
Non Laser Based
MJF
EBM
26
27. Binding Mechanisms in Laser Sintering
The various mechanisms for binding of materials in SLS can be summarized as:
• Solid Phase Sintering
– Binding takes place at surface, create necks b/w adjacent particle.
• Liquid Phase Sintering
– components with lower melting points are fused onto those with higher
melting points
• True Melting
– Near complete melting of powder, Also known as SLM
• Chemically Induced Binding
– Not very popular but accurate
27
28. Binding Mechanisms in Laser Sintering
Material Solid State
Sintering
Liquid State
Sintering
True Melting Chemically
Induced
Sintering
Polymers NO YES YES Rare
Metals YES YES YES YES
Ceramics YES YES YES YES
Composites NO YES NO YES
28
30. Motivation
• SLM is a cutting-edge technology that has the ability to dominate in the
fourth industrial revolution.
• SLM provides a small-scale manufacturing facility for highly customised
components for a variety of applications with virtually infinite design
flexibility.
• SLM has a number of disadvantages as well, including poor surface quality,
low reproducibility, low dimensional accuracy, and structural flaws.
• Since SLM is also used to create functional parts for machinery, dye moulds
for castings, the surface quality becomes critical, since any minute flaw in
the surface might reciprocate in the final casting, rendering the entire point
of employing SLM. *
30
* M. Leary, Surface roughness optimisation for selective laser melting (SLM): Accommodating
relevant and irrelevant surfaces, Laser Additive Manufacturing, Elsevier Ltd, 2017.
31. Literature Review
• SLM process is governed by a wide number of parameters, Each of them has
an influence on the development of the tracks*.
• Regrettably, their interplay is not always evident. That is why it is critical for
researchers to have a firm grasp on how to modify processing settings. At the
same time it was also stated that all these parameters may not be present or
influence the end product in every run in every machine*.
• Most of the researchers have studied the parameters related to laser or
geometry of the grains. Others have also studied the influence of temperatures
while manufacturing and during cooling of the fabricated parts.
• Different researchers have used different design of experiments and different
algorithms to propose their suggestions and results.
31
*(I. Yadroitsev and I. Smurov, “Selective laser melting technology: From the single laser melted track stability to 3D parts
of complex shape,” Phys. Procedia, vol. 5, no. PART 2, pp. 551–560, 2010, doi: 10.1016/j.phpro.2010.08.083.)
33. 33
Commercial Materials Used in SLM
Steel hot-work steel, stainless steel 316L, martensitic steel, tool steel
Titanium
Ti6Al4V
Ti6Al7Nb
Nickel based alloy
Inconel 718
Inconel 625
Copper Copper
Gold and Silver Gold and Silver
Aluminium Al6061, AlSi12Mg, AlSi10Mg
Composites
MMC
Fe-graphite, Ti- graphite/diamond, Ti-SiC, AlSi-SiC, AlMg-SiC, Co-WC,
Fe-SiC and Cu, Ni, Ti, C, Cu-TiC and Cu, Ni, Ti, B2C, Cu-TiB2
CMC ZrO2, Y2O3,, Al2O3 and TiO2, Al2C TiC/Al2O3, Al4.5Cu3Mg-SiC
34. Literature Review
• A critical review of the scientific literature available related to the
problems faced in SLM part fabrication is gone through and
summarized
• The literature is highly diversified and each researcher has taken one or
a few problems at a time and tried to propose a possible solution
• Thus for expediency the whole literature review is divided into two
categories
– Surface roughness
• Optimization Based
• Post processing Based
– Material related
34
35. 35
Author Material Tool used Findings
(Agarwala et
al., 1995)
bronze-nickel
powder
mixtures
Laser sintering of metals
using sacrificial element
Bronze being low melting point
metal melts and coats the nickel and
prevented the balling effect and
strong part was created.
(Wood et al.,
1996)
Polycarbonate spectral analysis and
ANOVA
Formal means of detecting,
quantifying and characterizing faults
in a manufacturing system were
proposed.
(Shi and
Gibson, 1998)
polymers Automatic Milling on
site in real time
proposed a robotic finishing system
in which a milling tool is held by a
robot and moved in accordance to
programmed paths generated from
the original CAD model data.
Surface Roughness Related Literature
36. Surface Roughness Related Literature
36
Author Material Tool used Findings
(Engel and
Bourell, 2000)
Ti-6Al-4V Compared the surface
roughness B/W degased
and non degased
sintered powder
Degased metal powderd sintered
part was more dense and had better
SR
(Campbell,
Martorelli and
Lee, 2002)
Polymer total nine categories of
profile tomography
measurement methods
were compiled
the Ra value is the most acceptable
surface roughness character
(Ramos and
Bourell, 2002)
SS and
Bronze
mixture
Surface polishing by
laser
peaks when melted fill the valleys
through gravity and improve the
average roughness. This is industry
accepted method now.
37. Surface Roughness Related Literature
37
Author Tool used Findings
(J. Kruth et al.,
2005)
examined the mechanical properties and surface
roughness of five different laser sintering
machines by creating a common shape
specimen had acceptable
dimensional accuracy and
close SR Values.
S.
No.
Machine Binding Mechanism Powder material
Parameters Layer
thickness/ laser power
PRODUCTION
TIME
1 3D Systems DTM Liquid phase sintering Polymer coated SS 80µm 10 W 3 + 24 hrs
2 Concept Laser Full melting Hot work tool steel 30 µm 200 W 9 hrs
3 Trumph Full melting Stainless steel 316L 50 µm 200 W 4.5 hrs
4 MCP-HEK Full melting Stainless steel 316 50 µm 100 W 8.5 hrs
5 EOS Partial melting Bronze based 20 µm 221 W 4.5 hrs
38. 38
Author Material Tool used Findings
(Shen, Gu and
Pan, 2006)
of 316
stainless
Experimentation They classified the balling process into three
sequential stages of aggregating, coarsening,
and balling. Further the effects of laser power
and scan speed on the balling phenomenon were
investigated and it was found that increasing
laser power and scan speed within a reasonable
range can reduce balling effect.
(Bacchewar et
al., 2007)
PA2200 Analysis of
variance and
optimization
In the case of upward-facing surfaces, layer
thickness been found to be significant
parameters. In downward- facing surfaces, layer
thickness, laser power has also been found to be
significant.
Surface Roughness Related Literature
39. 39
Author Material Tool used Findings
Wang et al.,
2009
SS Powder Taguchi orthogonal
array
SR of the end part fabricated by
SLM depends on each layer being
fabricated, overlap ratio and ED
(Jhabvala et
al., 2010)
gold powder
and WC-steel
coated
powder).
Scanning Strategies in
SLM, Experimental
numerical model was proposed to
evaluate scanning strategy. It was
able to detect overheated zones and
high temperature gradients.
(Yadroitsev
and Smurov,
2011)
SS grade 316L
and SS grade
904L
effect of hatch distance
on surface morphology,
Experimental
path width and effect of substrate
removal should be considered
together when selecting the hatch
spacing.
Surface Roughness Related Literature
40. 40
Author Materi
al
Tool used Findings
(Ragland, 2012) Ti-64 Analyze the surface
characteristics of parts
produced through traditional
manufacturing processes and
compare them to parts created
by Direct Metal Laser Sintered
machine
the parts as sintered were not of
minimum standards of the surgical
tools. Even after post finishing, the
parts still had much roughness than
required.
(Strano et al.,
2013)
Steel
316L
fabricated as truncheon
samples made by SLM.
Analysis was conducted at
different scales, by surface
profilometer and SEM.
proposed a mathematical model for
the prediction of real surface
roughness at different sloping
angles
Surface Roughness Related Literature
41. 41
Author Material Tool used Findings
(Vijay Arasu et al.,
2014)
LaserForm
ST-100 (SS)
L9 orthogonal array of
Taguchi design using
Laser power, Orientation
and Scan Spacing.
scan spacing was the most imperative
parameter in finalizing upward-facing
surface roughness.
(Patel, Patel and
Shah, 2015)
CL50WS,
hot work
steel
layer thickness and
orientation using
Factorial and ANOVA
surface roughness was influenced by layer
thickness, with orientation the roughness
increased while approaching the centre
value and then decreased at highest value
(Townsend et al.,
2016)
Polymers non- contact methods viz.
Focus Variation, Fringe
Projection Technique,
and Confocal Laser
Scanning Microscope and
one tactile
measurements on most of the occasions are
not reproducible and reliable. due to the
presence of inherent complexities in the
AM fabricated metal parts like voids,
uncertain peaks and other irregularities.
Surface Roughness Related Literature
42. 42
Author Material Tool used Findings
(Nhangumbe et
al., 2017)
-- Mathematics, Micro
milling
whole process of layer
manufacturing is divided into two
parts. The additive process and the
subtractive process which removes
the surplus material in every single
layer and in the production bed
itself. Thus SR will be improved.
(Baciu et al.,
2018)
Co-Cr-W
powder
alloy
1st sample kept as made
2nd was given sand blast
3rd was given sand blast
twice
concluded that sand blast improves
the surface quality as the surface
finish improved every time
Surface Roughness Related Literature
43. Surface Roughness Related Literature
43
Author Material Tool used Findings
(Sanaei, Fatemi
and Phan, 2019)
Ti-6Al-4V
alloy
Kolmogorov-Smirnov
(K-S) test on CT and
digital microscope
images
Surface defect variation was not
critical for Ti-6Al-4V under normal
conditions
(Mavoori,
Vekatesh and
Manzoor
Hussain, 2019)
PA2200
Polymer
L9 orthogonal array of
Taguchi design and
analysis
temperature had the maximum
influence on the SR, layer thickness
proved to have average influence
and laser power had least influence
on surface roughness.
44. 44
Author Material Tool used Findings
Ertuğrul et al.,
2020
AlSi10Mg HIP alone, HIP and T6
heat treatment and T6
heat treatment only
The results depicted that the HIP
does not affect the surface
characteristics much but increased
the inner porosity. The heat
treatment process relived the
stresses and mechanical properties
were increased.
Cho, S.-Y.; Kim,
M.-S.; Pyun, Y.-
S.; Shim, 2021
AISI 316L Ultrasonic nanocrystal
surface modification
(UNSM) technology
The conditions for the bombardment
of the nanocrystals were optimized
using RSM and ANOVA. the results
show that the surface smoothness
was significantly improved in the
treated samples as compared to the
untreated samples.
45. 45
Author Material Tool used Findings
El Hassanin et
al., 2021
AlSi10Mg laser re-melting of top
surface
The CO2 laser was used as a built
sample and the top surface was
subjected to interact with a high
energy laser beam to melt the crests
of the top surface and eventually fill
the troughs thus increasing the
surface quality.
46. 46
Author Tool used Findings
(Nesma T.
Aboulkhair, Marco
Simonelli, Luke
Parry, et al. 2019)
Fabrication and testing for
surface defects
The surface defects can be improved by
optimising the parameters and overall
properties of the Al alloys improved.
(Calignano et al.,
2013
L18 orthogonal array of
taguchi experimental design
using laser power, scan speed
and hatch spacing,
Shot peening
scan spacing proved to be the most
influencing for SR. To further improve the
SR of the parts, shot peening method was
proposed and it was concluded that the SR
was improved by 83% when the shot peening
was done at 8 bars of pressure
(Wei Li, Shuai Li,
Jie Liu et al. 2016)
heat treatments on the
microstructures and
mechanical properties
This study indicates that the microstructure
and mechanical properties of SLM-processed
AlSi10Mg alloy can be tailored by suitable
solution and artificial aging heat treatments.
AlSi10Mg Related Literature
47. 47
Author Tool used Findings
(A. Iturrioz & E. Gil1
& M. M. Petite & et
al. 2018)
Analysed thermal treatments to
samples manufactured by SLM
to investigate their effect on the
microstructure and mechanical
properties
The microstructure of AlSi10Mg alloy found
to be fine, the as-built sample achieved good
tensile strength and hardness values. After
heat treatments, there was decrease in tensile
strength and hardness up to 450 °C. However,
after heat treatment at 550 °C, it increased
(A.A Raus1, M.S
Wahab1, M.
Ibrahim1, K.
Kamarudin et al.
2017)
properties of SLM
manufactured AlSi10Mg
compared to conventionally
made high pressure die cast
A360 alloy
In comparison to the properties of a the
HPDC alloy A360F and HDPC alloy A360T6,
AlSi10Mg SLM samples show very high
values of hardness, yield strength, ultimate
tensile strength and elongation at break, while
for the Charpy impact energy test, there is
comparable although with a slightly lower
value.
AlSi10Mg Related Literature
48. Summary of Literature Review
• From the literature review, it is concluded that surface roughness and density
is a vital concern in SLM.
• The various techniques used for optimization are Taguchi, ANOVA, ANN and
genetic algorithm.
• The surface roughness is influenced by particle morphology as well as the
process parameters like laser power, scan speed, hatch distance, packaging
direction, powder shape, size and flow-ability, etc.
• While analyzing the literature, it is concluded that most of the research is
focused on laser parameters, hatch spacing, powder morphology and energy
density. Thus laser power, hatch spacing, scan speed and orientation of
scanning were selected as the factors to be studied and analyzed.
• Moreover, in many works of literature, there is a conflict between the
influence of laser power, scan speed and hatch spacing as a major contributor
as far as density and surface roughness are concerned.
48
49. Research Gap
• It has been found that work towards AlSi10Mg is limited, compared with other
materials. Most of the work has been done on mechanical strength, density and
sintering behaviour. The surface roughness has been explored by some researchers
but there is a conflict between the outcomes.
• It has been observed from the literature review that several pieces of research have
been done with limited process parameters on DMLS made part. But the study on
SLM is very limited. Thus, it is important to carry out systematic optimization of
SLM process parameters for AlSi10Mg material.
• The surface finish is an important criterion for dye and mould, automobile parts, and
the aerospace industry. AlSi10Mg being light, strong and durable material for these
sectors. But systematic multi-objective optimization of the SLM process was not
found.
• Most of the post-processing methods used by the researchers have been mechanical
ones like HIP, AFB, and laser remelting. Most of these methods lead to considerable
distortion of the dimensional accuracy.
49
50. Objectives
• To identify the process parameters which affect the surface roughness in
the laser sintering process using AlSi10Mg.
• To identify the factors affecting the density of the parts made by laser
sintering AlSi10Mg.
• To analyse the selected process parameters on the resulting properties
(surface roughness and density) through experimentation.
• To develop the mathematical relations between the selected set of
parameters and the desired outputs so that the behaviour can be
predicted for a different set of parameters.
• To optimize the selected process parameters for the best value of surface
finish and density under given conditions.
• To suggest for the reduction of surface roughness to improve the quality
of the output
50
51. Material and Methodology
• This section intend to define the research material and methodology for
the research work. Here the activities like selection of material,
equipment used, planning of experiments and data collection techniques
are discussed which include:
– Material
– Experimental Setup
– Selection of Process Parameters
– Measurement of Output Responses
– Design of experiments
– Analysis tools
– Post processing
51
52. Material
• Out of many materials as described,
AlSi10Mg holds a special status because of
its good casting properties and excellent
W/S ratio*.
• Also known as casting aluminium. It is
majorly an alloy of silicon and magnesium
which increases its hardness and strength
significantly and also gives a good fluid-
ability when in molten state.
52
*Lin-zhi Wang, Sen Wang, Jiao-jiao Wu,(2017) Experimental investigation on densification behavior of AlSi10Mg powders
produced by selective laser melting, Optics & Laser Technology, Volume 96,Pages 88-96,
Element Si Fe Cu Mn Mg Cr Ni Zn Ti P Pb Sn Al
Average
%
11.21 0.321 0.02 0.016 0.25 0.033 0.054 0.011 0.013 0.022 0.0028 0.0015 88.04
53. Material
• It is light weight, strong and can withstand
high loading conditions thus ideal for
aerospace industry as well as for automobile
sector. AlSi10Mg parts can be machined,
welded, can be treated on electric discharge
machine as well as electrochemical
machine. It can be subjected to wire erosion
process, polishing, coating and grinding.
• The material used in the present
investigation study is AlSi10Mg provided
by SLM solutions GmbH, Germany.
53
54. Experimental Setup
• The equipment employed to fabricate
the cast aluminium parts under
varying conditions is SLM®280 by
SLM solutions GmbH, Germany and
the facility is provided by amace
solutions, Bangalore.
54
55. Technical specifications of SLM setup used for Experimentation
Build Envelope (L x W x H) 280 x 280 x 365 mm³
3D Optics Configuration Twin (2x 700 W)
Build Rate (Twin 700 W) up to 88 cm³/h
Variable Layer Thickness 20 µm - 90 µm Min.
Feature Size 150 µm
Beam Focus Diameter 80 - 115 µm Max.
Scan Speed 10 m/s
Average Inert Gas Consumption in Process 2-5 l/min (argon)
Average Inert Gas Consumption Purging 70 l /min (argon)
E-Connection / Power Input 400 Volt 3NPE, 63 A, 50/60 Hz, 3,5 - 5,5 kW
Compressed Air Requirement ISO 8573-1:2010 [3:5:4]; 15 l/min (average) @ 6 bar
Dimensions (L x W x H) 2600 mm x 1200 mm x 2700 mm
Weight (without / incl. powder) approx. 1300 kg / approx. 1800 kg 55
56. Selection of Process Parameters
• From the previous investigations and studies by various eminent
researchers it was conclude that different set of process parameters
influence different output factors.
• For instance, roller speed in the chamber may influence the build-time
more than the density of the fabricated part and orientation of
fabrication may influence the part strength but may not affect the
porosity.
56
57. Selection of Process Parameters
• Keeping the objectives of the study clear it was deduced from the
literature review that the surface roughness and density are the functions
of laser power, hatch spacing, scan speed, bed temperature, layer
thickness, orientation of scanning, spot size, powder particle size and
shape, scan pattern and powder bed density.
• To study these many parameters in a single study is neither feasible due
to time and cost constraints nor possible by fewer researchers thus for
undergoing this study efficiently four parameters were selected namely
laser power, scan speed, hatch distance and orientation to characterize
the surface roughness and density.
57
58. Selected Process Parameters
• Laser Power: laser power is defined as the
total power in watts which is brought by the
laser beam on the powder grains. The
purpose of laser power is to generate heat
and melt the powder on which it strikes.
Units are Watts
• Scan Speed: Scan speed refers to the speed
at which the laser moves on the predefined
path on the powder bed. Too slow scan speed
can cause more interaction time of laser
beam with the powder causing overheating.
Too fast scan speed can cause under heating
The units of scan speed are mm/sec. 58
59. Selected Process Parameters
• Hatch Spacing: Hatch spacing is
defined as the mean distance between
the centres of two successive laser
spots in y-axis. There is always some
degree of overlap between the scans
which is desirable. The overlapping is
governed by the equation 𝑂𝐿 =
𝐻𝑆
𝐿𝑆𝑆
.
• Orientation: Orientation means the
direction of the scan vectors with
respect to x-axis.
59
60. Measurement of Output Responses
Measurement of Density
• Archimedes' Principle states that an object totally or partially submerged in a
fluid is buoyed (pushed) up by a force equal to the weight of the fluid that is
displaced by the immersed object.
• It has numerous applications, one of which is the determination of density. The
density of an object is what eventually determines whether the object will float
or sink.
• Measurement of the density of the test samples created by SLM of AlSi10Mg is
done using Archimedes principle in accordance with American Society for
Testing Materials (ASTM) Standards Designation: B311. This standard is
suitable for testing the density of Powder Metallurgy (PM) materials.
60
61. Measurement of Density
Distilled water at the temperature of
290C was used having the density of
0.9959
For AlSi10Mg, theoretical density is
2.68 g/cm3
ASTM Standards Designation: B311
– 17 This standard is suitable for
testing the density of Powder
Metallurgy (PM) materials
01
02
03
61
62. Measurement of Density
• According to Archimedes’ principle
the density can be calculated as
follows:
ρ =
𝑚𝑖𝑛 𝑎𝑖𝑟 X ρ
𝑙𝑖𝑞𝑢𝑖𝑑
𝑚𝑖𝑛 𝑎𝑖𝑟 −𝑚𝑖𝑛 𝑙𝑖𝑞𝑢𝑖𝑑
where,
– ρ liquid is the density of the liquid
generating buoyancy,
– m in air is the mass of the sample
in the air,
– m in liquid is the mass of the sample
in liquid. 62
63. Mass of specimen in air
(m in air)
Mass of the specimen in water
(m in liquid)
The density of water at 29 oC
(ρ liquid)
0.735 0.435 0.9959
63
The data for the sample specimen is shown in the table above
ρ =
𝑚𝑖𝑛 𝑎𝑖𝑟 X ρ𝑙𝑖𝑞𝑢𝑖𝑑
𝑚𝑖𝑛 𝑎𝑖𝑟 − 𝑚𝑖𝑛 𝑙𝑖𝑞𝑢𝑖𝑑
Substituting the above data in equation above the following result
is found.
ρ =
0.735 X 0.9959
0.735 − 0.450
= 2.245
Based on the above calculations the density for the entire sample
set is calculated.
64. Measurement of Surface Roughness
Categorially there are two ways to measure
surface roughness.
• One is the tactile measurement
instruments in which there is a probe
which is attached to a cantilever and the
probe is made to slide on the surface to be
measured for the roughness.
64
• Second type of SR measurement system
falls under the category of non-contact
type. A non-contact surface profile
measuring instrument uses light instead of
the stylus for measuring the surface
irregularities.
65. Measurement of Surface Roughness
• The surface roughness of the samples is measured
on Zeta 20 3D optical profilometer
• 3D microscope measures the details in a range of
height from the measuring plane and at each
measuring position it records the exact x-y location
and height. All this information is then merged to
create a complete 3D image.
• It is a fast, accurate and authenticated surface
measurement system. It has the ability to produce
3D images of the profile irregularities
65
66. Design of Experiments
• A well-defined design of experiments is the backbone of any research
study. The primary goal of healthy design of experiments is to get
maximum information from minimum number of experiments.
• Response surface methodology (RSM) is a statistical method for
experiential model building which is based on a fit on a polynomial
equation. By design of experiments, the objective is to optimize the
response variable(s) which is/are influenced by a number of independent
variables.
• The main application of RSM design is aimed at reducing the labour,
cost and time for expensive experimentations or runs and associated.
66
67. Design of Experiments
• The first step in RSM is to find a suitable approximation to the
relationship. The most common forms are low-order polynomials which
may be a first polynomial or second-order polynomial. For four factors,
second order polynomial can be assumed to be fit for interactions.
67
68. Box-Behnken Design
• Box-Behnken Designs (BBD) are a class of rotatable
or nearly rotatable second-order designs based on
three-level fractional factorial designs in response
surface methodology. For three factors its graphical
representation can be viewed in the form of a cube
that containing the central point and the middle points
of the edges
• The number of runs (N) required for the development
of Box-Behnken Design may be defined as N=2k
(k−1) +C, where k is number of factors and C is the
number of central points. BBD has an edge over CCD
as it does not contain arrangements for which all
factors are simultaneously at their upper or lowest
levels. So these designs are productive in avoiding
experiments performed under extreme conditions 68
69. Statistical Tool
• The statistical data which is collected for the analysis consist of two
parts one being the independent parameters which was generated by the
designing of experiments and other, the dependent parameters which
were generated after the experimentation
• Quantified results were tabulated for each set of independent parameters
the relation between these independent and dependent parameters was
conceded out using Analysis of Variance.
• Analysis of variance (ANOVA) is a statistical analysis tool. It splits the
observed collective variability found in the data set into two parts. One
being the systematic factors and other is random factors. The former
factors have a statistical influence on the given data set, while the later
do not.
69
70. Hypothesis Statement
As per the goals of the model discussed above, the Response Surface
Methodology is selected for the data generation. Before creating the design
of experiments, however, we can state hypothesis like all selected data sets
or groups will give same accuracy of result. This can be stated as follows:
Ho: There is no significant difference between the accuracy of different groups in
the data set i.e. the levels of laser power, scan speed, hatch spacing and orientation.
This can also be stated as all the input parameters in the study have equal amount
of influence on the response factors.
VERSES
H1: There is significant difference between the accuracy of different groups in the
data set i.e. the levels of laser power, scan speed, hatch spacing and orientation. In
other words at least one input factor is more significant in influencing the values of
response factors in comparison to other parameters. 70
71. Range of Parameters
71
The basis for the selection of the range of the parameters was governed
by equation
𝐸𝐷 =
𝑃
𝑉𝑥𝐻𝑥𝑇
Layer Thickness was kept constant at 60 microns
Variable Factors -1 0 1
Laser Power (P) in watts 300 350 400
Scan Speed (V) in mm/s 1500 1600 1700
Hatch Distance (H) in mm 0.1 0.175 2.5
Orientation (O) in degree 0 45 90
72. Planning of Experiments
• BBD model of Response surface methodology (RSM) used in the
development of the functional relationship between a response y,
and a number of associated control variables denoted by x1, x2,
…….xn
y = f (x1, x2) + ϵ
– Where ϵ represents the error in the response y and the surface represented
by f(xn) is called as response surface.
• The higher the degree of the polynomial, the more diligently the
Taylor series can approximate the actual function. It often suffices
to go only to quadratic level
𝑦 = 𝑎0 +
𝑖=1
𝑖=𝑛
𝑎𝑖𝑥𝑖 +
𝑖=1
𝑖=𝑛
𝑎𝑖𝑖𝑥2
𝑖 +
𝑖=1 𝑗=1
𝑖=𝑛 𝑗=𝑛
𝑥𝑖 𝑥𝑗 + 𝜖
72
73. Design of Experiments
• A total of 27 experiments with three central points and 24
factorial runs have been carried out at three levels. The plan of
the experiments have been depicted in the table .
73
76. Results
The aim is to
establish the
relationship
between the
process parameters
with the surface
roughness and
density in laser
sintering process
of AlSi10Mg.
76
For this 27
samples were
shaped as per the
design of
experiments
created using Box-
Behnken design of
Response Surface
Methodology.
.
The density was
checked using
Archimedes
principle in
accordance to
ASTM standards
B-311.
The average surface
roughness value
(Ra) of the
specimen was
employed. The test
was conducted five
times at each
surface and average
cumulative reading
was selected for the
analysis.
.
.
78. Analysis of Variance for Surface Roughness
• On the Basis on the values of process parameters and the output
responses summarized in the table on previous slide, the statistical
model has been developed using the regression analysis of RSM
using Minitab 17 software in order to define the relationship between
the two.
• The regression equation based on the analysis after eliminating the
insignificant terms is shown in equation below.
F1 = -126 - 0.433 * X1 + 0.196 * X2 + 844* X3
+ 0.000329 * X1*X1 - 0.000045 * X2*X2 -183
* X3*X3 + 0.000071* X1*X2 - 0.273* X1*X3 -
0.302 * X2*X3
78
79. ANOVA Table for Surface Roughness
Source DF Adj. SS Adj. MS F P R2 Remarks
Model 9 3433.25 381 45.48 0.000
0.960 F critical at 95% is
2.49
F critical < F model thus
the model is
adequate
Linear 3 3393.20 1131.07 134.85
Square 3 14.89 4.96
Interaction 3 25.15 8.38
Residual
Error
17 142.58 8.39
Lack of Fit 15 133.02 8.87 2.03 0.374
Pure Error 2 9.57 4.78 79
80. Graphical Representation of the Data
Residual versus Fitted Response for
Surface Roughness
Percentage Contribution of the Selected
Process Parameters on Surface Roughness
80
83. Analysis of Variance for Density
• A quadratic model is chosen to define the statistical model
because it fits the model nearly. The regression equation based
on the analysis after eliminating the insignificant terms is
shown in equation below.
F2 = -0.29 + 0.00010 *X1 + 0.00424 *X2 - 6.78* X3
+ 0.000001 *X1*X1 - 0.000002 *X2*X2 - 0.15* X3*X3
+ 0.000001 *X1*X2 + 0.00427 *X1*X3 + 0.00217 X2*X3
83
84. ANOVA Table for Density
84
Source DF Adj SS Adj MS F-Value P-Value R2 Remarks
Model 9 0.287358 0.031929 29.16 0.000 93.92 F critical at 95%
is 2.49
F critical < F
model thus the
model is
adequate
Linear 3 0.283718 0.094573 86.38 0.000
Square 3 0.001559 0.000520
Interaction 3 0.002080 0.000693
Residual Error 17 0.018613 0.001095
Lack-of-Fit 15 0.008519 0.000568 0.11 0.997
Pure Error 2 0.010094 0.005047
Total 26 0.305971
85. Graphical Representation of the Data
Residual versus Fitted Response for
Density
Percentage Contribution of the Selected
Process Parameters on Density
85
88. Result of Hypothesis
88
Ho: There is no significant difference between the accuracy of
two different groups in the data set i.e. the levels of laser power,
scan speed, hatch spacing and orientation. This can also be stated
as all the input parameters in the study have equal amount of
influence on the response factors.
H1: There is significant difference between the accuracy of two
different groups in the data set i.e. the levels of laser power, scan
speed, hatch spacing and orientation. In other words at least one
input factor is more significant in influencing the values of
response factors in comparison to other parameters
89. Optimization
89
The multi-objective genetic algorithm was employed with respect to following conditions
– Minimize F1 = SR(φ)
– Maximize F2= D(φ)
Where φ is [X1, X2, X3, X4]
• Subject to
• 300≤X1≤400
• 1500≤X2≤ 1700
• 0.1≤X3≤0.25
• 0≤X4≤ 90
SR
F1
Density
F2
Laser Power
P
Scan Speed
V
Hatch Spacing
H
Orientation
O
16.57 2.52 399.94 1554.36 0.100 0.48
91. Post Processing
• Metal-based additive manufacturing techniques, despite their bright future,
may be limited in their potential applications by the relatively low surface
quality, porosity, and residual stresses of the produced objects.
• To enhance both their topological and physical characteristics, components
made using additive manufacturing processes must go through a post-
processing step.
• The characteristics can be improved by various post-processing techniques
like special heat treatment (HT), Hot Isostatic Pressing (HIP) electrochemical
polishing (ECP), media blasting or tumbling or sandblasting (SB) and
ultrasonic excitation (ESE) to name a few.
• The choices of methods depend on the material to be sintered, sintering
technology, application requirements, geometry complexity, size of parts and
required surface quality and polishing technologies available. 91
92. Post Processing (Chemical Treatment)
• The post-process utilized in the present study is chemical polishing. The
process has been carried out by some researchers on ABS materials
made by FDM (Galantucci, Lavecchia and Percoco, 2009).
• The impact of chemical polishing on the AlSi10Mg is explored in the
study.
• The samples were degreased in distilled water before chemical polishing
to remove surface impurities. The chemical bath was used in a one-litre
beaker and controlled at 95 degrees Celsius (± 10).
• Each sample was hand stirred in the chemical bath for 15 minutes with
an interval of 5 minutes each.
• The samples were tested for surface roughness before and after the
chemical treatment.
• The samples were tested for chemical composition before and after the
chemical treatment on the spectrometer as well.
92
93. Post Processing (Chemical Treatment) S No. Time Ra Height
1 0 15.291 6.532
2 5 6.121 6.49
3 10 5.2 5.961
4 15 4.731 4.922
93
• A significant improvement in the surface morphology was noted in the first 5
of the chemical treatment.
• Further, the main effect of the chemical treatment is on peaks thus the overall
smoother surfaces have been achieved this can be judged by observing the
trends of Ra.
• Also when the peaks of the surface got dissolved the effect of the chemical
treatment became less significant in the later stage of the treatment.
95. Conclusion
• Hatch spacing has the maximum influence followed by laser power, scan
spacing on surface roughness. Orientation is an almost negligible influence
on SR.
• Lower values of hatch spacing tend to increase the surface finish and with
an increase in laser power, the surface finish increased significantly.
• Scan speed and orientation do have not as much of an effect on surface
characteristics of laser sintered parts.
• Density is inversely proportional to hatch spacing. Higher values of hatch
spacing result in reduced density and visa- versa.
• Laser power is a direct function of density. The higher the Lase power
higher is the density under given circumstances. Much high values of laser
power may burn the powder and no sintering will take place. 95
96. Conclusion
• Faster scan speed leads to less exposure and thus density deteriorates. Much
slow speeds can lead to more heat accumulation and overheating.
• The chemical treatment of the surface proved to be effective to improve the
surface finish. Surface finish of the sample improved from 15 microns to 4
microns.
• There is no chemical change found in the part which was confirmed by
chemical testing on the spectrometer.
• The surface roughness improved drastically in the first 5 minutes of the
chemical treatment. The interaction beyond 10 min may result in loss of final
dimensions of the parts although uniformly.
• The prolonged interaction of the AlSi10Mg AM fabricated part with the
chemical bath can lead to dimensional loss.
96
97. Scientific Contribution
• For sintering AlSi10Mg high energy density (50 -70 J/mm3) is used
which means high energy input and slow fabrication. In this study, the
sintering is proposed as medium energy (40 – 50 J/mm3) density yet
with the ability to achieve high density and better surface finish and that
too at a faster pace.
• A high density of the fabricated parts can be achieved by optimizing the
process parameters
• Increased productivity and saved energy
• Improve surface finish using chemical polishing of Laser Sintered parts
97
98. Limitations of the study
• Only four input factors were considered for the optimization study. The
increased number of process parameters would have increased the
experimental runs which would have increased the scale of the study
significantly.
• The optimization is carried out on DOE based technique but other methods
like ANN, GA, scatter search method, etc. can also be explored and
compared.
• The influence of process parameters on mechanical properties is also not
carried out. The influence of other input factors and effect on remaining
response factors can be carried out in phase manner in subsequent studies.
98
99. Future Scope
• The future research may also include the modelling of the thermal
barriers that are usually deposited on laser sintered parts.
• By changing the orientation of the laser beam the lattice structure
changes the effects of which have not been explored sufficiently till
date.
99
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103
104. Outline of the Thesis
Chapter 1
Introduction
• The current one begins with the background to the field of research that leads the reader to the
research problem addressed in additive manufacturing. Next, the relevance of the problem area is
discussed. The additive manufacturing processes are discussed. The materials used in the SLM
process are outlined. The working principle of the SLM is explained and after that delimitation of
the thesis. Chapter 1 ends with an outline of the thesis.
Chapter 2
Literature review
• Reviews common additive processes with emphasis on a description of Selective Laser Sintering
(SLS) technology and Selective Laser Melting (SLM) which is considered one of the most
versatile of all additive manufacturing techniques. During the SLM process, the main fabrication
parameters which influence the quality of the sintered part are described. Some of the common
materials used to produce parts by SLM are presented. The problems found in the parts produced
through the sintering process of AlSi10Mg are mentioned in this chapter. Additionally, some
previous studies of composite materials used in SLM are reviewed.
– The detailed literature survey meet objective 1 and objective 2 of the study. The factors effecting
surface roughness and density in laser sintered parts were identified based on the previous
researches and literature which became the basis of the current study. 104
105. Outline of the Thesis
Chapter 3
Methods and Materials
• This chapter deals with the material selection, selection of process parameters for the
experimentation and the final setup of the experiments.
Chapter 4
Scheme of Experiments
• This chapter deals with the creation of the design of experiments to conduct the final
experiments. It gives the full details of the process parameters, the basis for the selection
of the parameters, their range, data acquisition techniques i.e. measurement of density and
surface roughness.
– Objective 3 is to analyse the selected process parameters through experimentations. This objective is
meets in this section as the piolet experiments were done to check the feasibility of the fabrication
parameters and after satisfactory results design of experiments was created to conduct the final
experiments. The parts were then put to tests to measure the surface roughness and density
quantitatively for further analysis. 105
106. Outline of the Thesis
Chapter 5
Results and Discussions
• In this chapter, the results of the analysis are thoroughly discussed and
elaborated. The surface characterization of surface roughness and density is
explained as per the results of the analysis. The significance of each input
parameter is discussed for each response factor. Finally, the optimization
results are shown as per the regression equation using a multiobjective
genetic algorithm tool in MATLAB. The results of the confirmation tests are
also discussed.
– Objective 4 is related to derive the mathematical relation between the input
factors and output factors which is met by analysing the factors using ANOVA.
This method gave the relation between the input factors and the output factors.
– Objective 5 is also achieved in this section as the optimization was carried out
on Matlab interface
– Objective 6 is achieved in this section by utilising chemical polishing as post
processing method to increase the surface finish.
106
107. Outline of the Thesis
Chapter 6
Conclusions, Contributions and Future Scope
• Concludes the thesis by summarizing the contributions and findings of the research
and proposing areas for further study
• References
107
