SlideShare a Scribd company logo
Department of Mechanical Engineering
Academic Year: 2023-24
OPTIMIZATION OF PRINTING PARAMETERS IN
FUSED DEPOSITION MODELLING FOR IMPROVING
PART QUALITY AND MECHANICAL STRENGTH
21P35A0312 - M.V.K.RAHUL
20P31A0317 - C.ASHISH RAM
20P31A0332 - K.N.S.M.KIRAN
20P31A0333 - K.SRINIVAS
Under the Guidance of
Dr.CH.V.V.M.J.SATISH
Associate Professor
M.Tech, Phd
BATCH – 07:
Contents
• Abstract
• Literature Review
• Introduction
• Estimated CO-PO mapping
• Plan of Action
• Cost estimation Report
• Project Overview
• Methodology and Experimentation
• Results
• Conclusion
• References
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
2
Abstract
This project seeks to optimize printing parameters in Fused Deposition Modeling
(FDM) to enhance part quality and improve the mechanical strength of the printed
part. FDM is a widely adopted 3D printing technology, and improving its efficiency
is crucial for advancing additive manufacturing. The project aims to systematically
investigate various printing parameters and their interactions to find an optimal
configuration that balances part quality, production time, and mechanical strength.
Through experimental research and analysis, the project aims to provide valuable
insights and guidelines for users aiming to maximize the benefits of FDM
technology, with a focus on fast and quality prototype production.
We are aiming to build a low cost 3d printer by purchasing various parts and
assembling them to perform our experimentation. By using CAD design and Slicing
software, we are going to vary the various process parameters like layer height,
extrusion temperature etc., and perform Design of Experiments(Taguchi Approach) to
find the optimal parameters suitable for our 3d printer built in order to obtain good
surface finish and improved mechanical strength of the printed parts.
5/14/2024 3
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
Introduction
5/14/2024 4
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
Additive manufacturing (AM), commonly known as 3D
printing, is the process of creating parts by accumulating material
layer upon layer, starting directly from a computer-aided design
model. There are many prominent advantages of AM that can be listed
out, such as direct manufacturing process without molds, unrestricted
to the complexity of product structure, unlimited in innovative and
creative design, high utilization of material and eco-friendly.
Nowadays, the use of 3D printing is increasingly popular not only
in prototype phase but also in finished product, in various fields
from aerospace, automotive to medical. Parallel to the rapid increase of 3D
printing use, it is essential to have an instruction for the optimal
process parameters to attain qualified products regards to
efficiency. In addition, due to the principle of 3D printing is adding
layer by layer material in order to make a finished part, product
mechanical property is the important quality criteria should be
considered.
Thus, investigating the effect of each process parameters on mechanical characteristics
of the FDM parts helps to adjust level of process variables leading to improvement in
quality of parts. There are various factors such as orientation angle, raster angle, layer
thickness, shell thickness, infill pattern, infill density, extrusion temperature, printing
speed which affect the ultimate tensile strength and surface finish for finished product.
The levels of these process parameters can be varied using a slicing software and by
finding the optimal levels of these process parameters, the response output variables
which are the mechanical properties of the printed parts can be optimized.
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
5
Literature
In the past several years, researchers have examined the outcomes of 3D printing parameters on
key metrics of FDM to improve the condition of the part by maximizing yield strength and
ultimate tensile strength, among other mechanical properties.
1. Hassanifard and Hashemi [1] studied the effect of part’s build orientation and raster angle
on the strain-life fatigue of specimens made of Ultem 9085, polycarbonate (PC), and
polylactic acid (PLA). Parts were created based on ASTM D638-14 and ASTM D790-17
standards. The authors concluded that infill density affected the mechanical properties of
the printed part.
2. The aim of the work reported by Verbeeten et al. [2] was to investigate the strain-rate
dependence of the yield stress for tensile samples made of PLA, based on ISO 527-2
standard. Printing speed, infill orientation angle, and bed temperature were modified. One
of the conclusions of the study was that a change of infill orientation angle from 0 to 90°
provided anisotropic effects to the pieces.
5/14/2024 6
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
3. Zhao et al. [3] explored the effect of printing angle and layer thickness on the mechanical
properties of specimens made of PLA. The standard used to fabricate the units was ISO 527-2-
2012. Tensile strength increased with higher values of printing angle and reduced ones of layer
thickness.
4. Tanoto et al. [4] evaluated dimensional accuracy, processing time, and tensile strength of 3D
printed components. The components were made of ABS, using FDM technology. The printing
plane and the orientation angle were selected as the response variables to be analyzed. The
specimens employed in the experimental trials belong to type IV, according to the ASTM D638-
02 standard. Printing time diminished when the part was oriented in the XZ plane at 90°. This
orientation also provided a specimen’s length value closer to the one of the ASTM standard.
5. The work of Alafaghani et al. [5] presented an experiment to determine the values of infill rate,
infill pattern, the orientation of the part, and layer thickness that enhanced dimensional accuracy
and mechanical properties of specimens made of PLA. The part design followed type IV
specifications according to the ASTM D638-15 standard. Lower values of fill density and shell
thickness and higher values of layer thickness and feed rate reduced the measured values.
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
7
6. Huynh et al. [6] considered the effect of infill rate, infill pattern, and layer thickness on the
dimensional precision of parts made of PLA using FDM. The piece was a CAD model created
by the authors, and an orthogonal array L27 was applied, along with a fuzzy approach to
optimize printing parameters.
7. The work of Padhi et al. [7] shows a comparison between the dimensional deviation of
printed specimens from the dimensions of a CAD model. An L27 orthogonal array allowed to
modify the infill angle, raster width, air gap, orientation of the part, and layer thickness. The
material of the specimens is ABS P400. A medium value for layer thickness and raster width,
the greatest one for the air gap and the least for orientation and raster angle, granted the
highest dimensional precision.
8. Mohamed et al. [8] investigated the dimensional accuracy of specimens made of a PCABS
blend, employing FDM. The process parameters that were modified are raster angle, raster
width, air gap, part orientation, layer thickness, and the number of contours. The geometry of
the specimens is according to the standards ASTM D5418-07 and ASTM D7028-07e1. The
layer thickness was the factor that affected all the responses.
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
8
Estimated CO-PO Mapping
PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO1
0
PSO
1
PSO
2
Pso2
CO1 3 2 3 2
CO2 3 3 2 3 2
CO3 3 1 2 2 3 3 2
C04 3 3 3 2 3 1 1
C05 3 2 3 2 3 1 2 3 2
C06 3 3 3 2 3 3 3
5/14/2024 9
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
Plan of Action
5/14/2024 10
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
Sl. No Date/Duration Description
1 Week-1
18-01-24 to 24-01-24
Define Project Scope and Objectives:
Clearly outline the project's goals, including the
specific printing parameters to be optimized, cost
considerations, etc.,
2 Week-2
25-01-24 to 31-01-24
Cost Estimation and Budgeting:
Develop a detailed cost estimation for the project,
considering expenses related to materials, equipment
and other relevant factors.
3 Week-3
01-02-24 to 07-02-24
Review Existing Literature:
Conduct an in-depth review of relevant literature to
understand about our project goals
4 Week-4
08-02-24 to 14-02-24
Learn basic Designing for 3d printing:
Learn and practice designing simple 2d and
3d figures like cubes and cylinders in ONSHAPE
Sl. No Date/Duration Description
5 Week-5
15-02-24 to 21-02-24
Learn basics in Slicing Software:
Learn and Practice to use Ulti maker Cura Slicing
software and about the various parameters that can be
controlled for 3d printing
6 Week-6
22-02-24 to 28-02-24
Learn about Design of Experiments(DOE):
Study about the Design of Experiments(DOE) and
Taguchi Approach and practice using it in Minitab
7 Week-7
29-02-24 to 06-03-24
Purchase and Assemble the 3d Printer:
Purchase various parts and components and assemble
them to build our 3d printer
8 Week- 8
07-03-24 to 13-03-24
Practice printing on the 3d printer:
Practice designing and give sample prints in our 3d
printer
9 Week- 9
14-03-24 to 20-03-24
Designing a standard specimen for
experimentation:
Designing a standard test specimen for experimentation
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
11
Sl. No Date/Duration Description
10 Week- 10
21-03-24 to 27-03-24
Printing the test specimens :
Printing all the required test specimens with
varying parameters on the 3d printer
11 Week- 11
28-03-24 to 03-04-24
Surface Roughness testing of printed parts:
Testing and obtaining required values of surface
roughness for the printed parts with Surface
roughness testing machine
12 Week- 12
04-04-24 to 10-04-24
Ultimate Tensile strength testing of printed
parts:
Testing the printed parts in UTM for obtaining the
strength values of all printed parts
13 Week- 13
11-04-24 to 17-04-24
Analysis of the results with Taguchi Approach:
Analysis and application of Taguchi Statistical
Approach to obtain optimal parameters
14 Week- 14
18-04-24 to 24-04-24
Verification and Document preparation:
Verification of the end results and document
preparation for the project
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
12
Budget estimation
Sl.
No
Equipment/Parts Quantity Price per
Quantity
Total Price in INR
1 Print material 1 800 800
2 Nozzle Set 1 600 600
3 Stepper Motors 3 700 2100
4 Controller Board 1 700 700
5 Frame 1 3000 3000
6 Motion Components 1 1200 1200
7 Power supply unit 1 1000 1000
8 Print Bed 1 400 400
9 Extruder 1 5500 5500
10 Feeder System 1 1500 1500
5/14/2024 13
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
Total Budget Estimation = Rs.17000
Project Overview
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
14
PARAMETER OPTIMIZATION IN FUSED DEPOSITION MODELLING:
In order to find the optimal levels of parameters for our assembled Any Cubic
Kobra 2 Neo 3D Printer for obtaining high mechanical strength and good
surface finish, we have considered 3 factors which are majorly influencing
the mechanical properties i.e., strength and surface roughness of the 3d
printed parts. The 3 factors are layer height, infill percent and extrusion
temperature. From the previous studies done by different researchers, layer
height is the main influencing factor behind the surface roughness of the 3d
printed parts and the factors layer height and infill percent and extrusion
temperature influence the strength of the printed parts.
• Layer Height:
• The thickness of each layer of deposited material is called the ‘layer height’.
• The surface quality of the finished part is proportional to how small the layer height
is; smaller layer heights result in smother surface finishes.
• For FDM printers, the number of layers is one
indicator of how much time a 3D print will take.
Choosing a smaller layer height will divide a 3D
model into more layers, increasing the print time.
For Any Cubic Kobra 2 Neo 3D Printer, the
recommended layer height in Cura is 0.2mm. And
Our nozzle diameter is 0.4mm. So, we have taken
3 levels of layer height from 0.2-0.3 mm.
Layer height : Level-1 : 0.20mm
Level-2 : 0.25mm
Level-3 : 0.30mm
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
15
• Infill Density:
• Infill density is the “fullness” of the
inside of a part. In slicers, this is usually
defined as a percentage between 0 and 100.
Infill Density : Level-1 : 15%
Level-2 : 60%
Level-3 : 100%
• Extrusion Temperature:
• Extrusion temperature is the temperature the
extruder heats to during your print.
• PLA melts at extrusion temperatures from about
180°C.The suggested temperature is 200 °C and the
Maximum temperature the printer can attain is 260 °C
Extrusion Temperature : Level-1 : 200 °C
Level-2 : 230 °C
Level-3 : 260 °C
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
16
Design Matrix for Experimentation
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
17
S. No. FACTORS LEVEL 1 LEVEL 2 LEVEL 3
1 LAYER HEIGHT 0.1 0.25 0.3
2 INFILL PERCENTAGE 15 60 100
3 EXTRUSION
TEMPERATURE
200 230 260
Taguchi Statistical design in Minitab
Runs. A B C
1. 1 1 1
2. 1 2 2
3. 1 3 3
4. 2 1 2
5. 2 2 3
6. 2 3 1
7. 3 1 3
8. 3 2 1
9. 3 3 2
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
18
To find the optimal levels of the printing parameters i.e., layer height, infill
percent and extrusion temperature, we are considered 3 levels for each factor
following low, medium and high levels of the respective printing parameters as per
the specifications of the 3d printer.
We used Design of Experiments (D.O.E) for
finding the optimal parameter levels. In D.O.E,
we followed L9 Orthogonal Array from Taguchi
Design Approach and with the help of Mini Tab
Statistical Software, we found out the optimal
levels of the considered three factors.
Taguchi Design:
L9 Orthogonal Array for 3 factors with 3 levels:
In this design, Factor A is Layer Height with 3
different levels 1,2,3.Factor B is Infill Percent with
3 different levels 1,2,3.Factor C is Extrusion
Temperature with three different levels 1,2,3
columns of L9 (3^4) array: 1 2 3
L9 0rthogonal Array (3 factors, 3 levels)
Runs Layer Height (mm) Infill Density (%) Extrusion
Temperature (°C)
1 0.20 15 200
2 0.20 60 230
3 0.20 100 260
4 0.25 15 230
5 0.25 60 260
6 0.25 100 200
7 0.30 15 260
8 0.30 60 200
9 0.30 100 230
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
19
Methodology and Experimentation
• Sample preparation
• The specimens used in this study to evaluate the mechanical properties are
modelled based on American Society for Testing and Materials ASTM D638 type I
standards for plastic tensile testing. All the specimens were printed using PLA
filaments and a Any Cubic Kobra 2 Neo 3D Printer.
ASTM D638 type I
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
20
• Designing and Slicing:
• We designed the specimen in ONSHAPE CAD Software as per its standard
dimensions and sliced it in UltiMaker CURA Slicing software by varying the levels of
parameters i.e., layer height, infill density and extrusion temperature each time as
per the Taguchi L9 Orthogonal Design Approach.
• We made 9 G-codes for 9 experimental runs and printed the sample specimens.
slicing of ASTM D638 type-I in UltiMaker Cura
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
21
• 3D Printing of the Specimens
3d printed specimens
assembled 3d printer
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
22
• Tensile test on Universal Testing Machine(UTM)
UTM tensile testing of specimen on UTM
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
23
Experimental Results of Tensile Test
Runs Layer
Height
(mm)
Infill Density
(%)
Extrusion
Temperature (°C)
Printing
Time
(min)
Ultimate Tensile
Strength (Mpa)
1 0.20 15 200 57 133.173
2 0.20 60 230 61 135.096
3 0.20 100 260 64 140.865
4 0.25 15 230 51 133.653
5 0.25 60 260 53 136.538
6 0.25 100 200 56 141.827
7 0.30 15 260 46 133.659
8 0.30 60 200 46 138.942
9 0.30 100 230 49 139.909
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
24
• Surface Roughness Test using Surface
Roughness Tester
MEXTECH SRT-6200 Surface Roughness Measuring Ra for a specimen
Tester
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
25
Experimental Results of Surface
Roughness Test
Runs Layer
Height
(mm)
Infill Density
(%)
Extrusion
Temperature
(°C)
Printing
Time (min)
Surface
Roughness – Ra
(microns)
1 0.20 15 200 57 10.230
2 0.20 60 230 61 9.456
3 0.20 100 260 64 5.354
4 0.25 15 230 51 10.390
5 0.25 60 260 53 9.027
6 0.25 100 200 56 10.780
7 0.30 15 260 46 7.971
8 0.30 60 200 46 9.758
9 0.30 100 230 49 5.939
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
26
Results
• Taguchi Analysis: Ultimate Tensile Strength (MPa) versus Layer Height (mm),
Infill Percent (%), Extrusion Temperature(0C)
• Optimal Levels for Layer Height – 0.30mm, Infill Percent – 100%,
Extrusion Temperature - 2000C for improved mechanical strength.
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
27
• Taguchi Analysis: Surface Roughness Ra (microns) versus Layer Height (mm),
Infill Percent (%), Extrusion Temperature(0C)
• Optimal Levels for Layer Height – 0.25mm, Infill Percent – 15%, Extrusion
Temperature - 2000C for improved Surface Quality.
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
28
• Taguchi Analysis: Ultimate Tensile Strength (MPa), Average Surface Roughness Ra
(microns) versus Layer Height (mm), Infill Percent (%), Extrusion
Temperature(0C)
• Optimal Levels for Layer Height – 0.25mm, Infill Percent – 100%,
Extrusion Temperature - 2000C for nominal values of Surface Quality and Strength.
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
29
Conclusion
The conclusions of our Project Work “Optimization of 3D Printing Parameters
for improving Surface Quality and Mechanical Strength” are as follows:
1. For obtaining Printed parts with high mechanical strength, the optimal levels of
the process parameters were found out as: Layer height: 0.3 mm; Infill Percent :
100% ; Extrusion Temperature : 2000C
and Infill Density is the process parameter which has more influence on the
Mechanical Strength of the printed parts.
2. For obtaining Printed parts with good surface quality i.e., lower values of Surface
Roughness, the optimal levels of the process parameters were found out as: Layer
height: 0.25 mm; Infill Percent : 15% ; Extrusion Temperature : 2000C
and Extrusion Temperature is the process parameter which has more influence on
the Surface Quality of the printed parts.
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
30
3. For obtaining printed parts with nominal values of strength and surface roughness
i.e., average values of strength and surface roughness, the optimal levels of the
processing parameters are:
Layer height: 0.25 mm; Infill Percent : 100% ; Extrusion Temperature :
2000C
and Infill Density is the process parameter which influences both Strength and
Surface Quality of the printed parts.
Through this research work, we would suggest a Full Factorial DOE
Statistical Approach for well prediction of the response for future work. For a Full
Factorial DOE, experimenting with 3 factors with 3 levels each would require 27
experimental runs which would consume more material and power but it would
give more accurate results than the Taguchi Methodology as here we only did 9
experimental runs for 3 factors with 3 levels each. It is also suggested to develop a
Regression Model following the Full factorial DOE method to predict the
Strength and Surface Roughness of the printed parts mathematically.Also, a
smaller range of Layer Height (<0.20mm) should be addressed and investigated.
This research also suggests that effectiveness of orientation angle and the effect of
Printing Speed should be included in the future research.
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
31
References
[1] Hassanifard S, Hashemi SM (2020) On the strain-life fatigue parameters of
additive manufactured plastic materials through fused filament fabrication
process. Additive Manufacturing 32:100973. https://doi.
org/10.1016/j.addma.2019.100973
[2] Verbeeten WMH, Lorenzo-Bañuelos M, Arribas-Subiñas PJ (2020)
Anisotropic ratedependent mechanical behaviour of poly lactic acid (PLA)
processed by material extrusion. Additive Manufacturing 31:100968.
https://doi.org/10.1016/j.addma.2019.100968
[3] Zhao Y, Chen Y, Zhou Y (2019) Novel mechanical models of tensile strength
and elastic property of FDM AM PLA materials: experimental and theoretical
analyses. Mater Des 181:108089. https:// doi.org/10.1016/j.matdes.2019.108089
[4] Tanoto YY, Anggono J, Siahaan IH, Budiman W (2017) The effect of
orientation difference infused deposition modeling of ABS polymer on the
processing time, dimension accuracy, and strength. in: AIP Conference
Proceedings. https://doi.org/10.1063/1.4968304
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
32
[5] Alafaghani A, Qattawi A, Alrawi B, Guzman A (2017) Experimental
optimization of fused deposition modelling processing parameters: a design-for-
manufacturing approach. Procedia Manufacturing 10:791–803.
https://doi.org/10.1016/j.promfg.2017.07.079
[6] Huynh HN, Nguyen AT, Ha NL, Ha Thai TT (2017) Application of fuzzy
Taguchi method to improve the dimensional accuracy of fused deposition
modelling processed product. In: Proceedings 2017 International Conference on
System Science and Engineering, ICSSE 2017.
https://doi.org/10.1109/ICSSE.2017. 8030847
[7] Padhi SK, Sahu RK, Mahapatra SS, Das HC, Sood AK, Patro B, Mondal AK
(2017) Optimization of fused deposition modelling process parameters using a
fuzzy inference system coupled with Taguchi philosophy. Additive Manufacturing
5:231–242. https://doi.org/10.1007/s40436-017-0187-4
[8] Mohamed OA, Masood SH, Bhowmik JL (2016) Optimization of fused
deposition modelling process parameters for dimensional accuracy using I-
optimality criterion. Meas J Int Meas Confed 81: 174–196.
https://doi.org/10.1016/j.measurement.2015.12.011
5/14/2024
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY
33
5/14/2024 34
ADITYA COLLEGE OF ENGINEERING &
TECHNOLOGY

More Related Content

Similar to Batdwcwcdwcwcwcewcewcewxewecwcewcch-7.pptx

A Review on Finite Element Analysis of Automobile roof header Manufactured By...
A Review on Finite Element Analysis of Automobile roof header Manufactured By...A Review on Finite Element Analysis of Automobile roof header Manufactured By...
A Review on Finite Element Analysis of Automobile roof header Manufactured By...
ijiert bestjournal
 
IRJET- Effect of Gasoline Exposure on the Mechanical Properties of PLA an...
IRJET-  	  Effect of Gasoline Exposure on the Mechanical Properties of PLA an...IRJET-  	  Effect of Gasoline Exposure on the Mechanical Properties of PLA an...
IRJET- Effect of Gasoline Exposure on the Mechanical Properties of PLA an...
IRJET Journal
 
Ijmer 46064551
Ijmer 46064551Ijmer 46064551
Ijmer 46064551
IJMER
 
Optimization of Cutting Parameters Using Genetic Algorithm and Particle Swar...
Optimization of Cutting Parameters Using Genetic Algorithm  and Particle Swar...Optimization of Cutting Parameters Using Genetic Algorithm  and Particle Swar...
Optimization of Cutting Parameters Using Genetic Algorithm and Particle Swar...
IJMER
 
1 i18 ijsrms0206178-v2-i6-prasad diwanji-30nov15
1 i18 ijsrms0206178-v2-i6-prasad diwanji-30nov151 i18 ijsrms0206178-v2-i6-prasad diwanji-30nov15
1 i18 ijsrms0206178-v2-i6-prasad diwanji-30nov15
vishwajeet potdar
 
CHARACTERIZATION AND ANALYSIS OF MECHANICAL PROPERTIES FOR 3D PRINTING MATERIALS
CHARACTERIZATION AND ANALYSIS OF MECHANICAL PROPERTIES FOR 3D PRINTING MATERIALSCHARACTERIZATION AND ANALYSIS OF MECHANICAL PROPERTIES FOR 3D PRINTING MATERIALS
CHARACTERIZATION AND ANALYSIS OF MECHANICAL PROPERTIES FOR 3D PRINTING MATERIALS
IRJET Journal
 
Experimental Studies on Effect of Layer Thickness on Surface Finish using FDM
Experimental Studies on Effect of Layer Thickness on Surface Finish using FDMExperimental Studies on Effect of Layer Thickness on Surface Finish using FDM
Experimental Studies on Effect of Layer Thickness on Surface Finish using FDM
IRJET Journal
 
Investigation of post processing techniques to reduce the surface roughness o...
Investigation of post processing techniques to reduce the surface roughness o...Investigation of post processing techniques to reduce the surface roughness o...
Investigation of post processing techniques to reduce the surface roughness o...
iaemedu
 
Investigation of post processing techniques to reduce the surface
Investigation of post processing techniques to reduce the surfaceInvestigation of post processing techniques to reduce the surface
Investigation of post processing techniques to reduce the surface
iaemedu
 
A Review: Fused Deposition Modeling – A Rapid Prototyping Process
A Review: Fused Deposition Modeling – A Rapid Prototyping ProcessA Review: Fused Deposition Modeling – A Rapid Prototyping Process
A Review: Fused Deposition Modeling – A Rapid Prototyping Process
IRJET Journal
 
Process parameter optimization of SLM process and application of Taguchi appr...
Process parameter optimization of SLM process and application of Taguchi appr...Process parameter optimization of SLM process and application of Taguchi appr...
Process parameter optimization of SLM process and application of Taguchi appr...
ijsrd.com
 
Manufacturing Process Simulation Based Geometrical Design for Complicated Parts
Manufacturing Process Simulation Based Geometrical Design for Complicated PartsManufacturing Process Simulation Based Geometrical Design for Complicated Parts
Manufacturing Process Simulation Based Geometrical Design for Complicated Parts
Liu PeiLing
 
30120130406023 2-3
30120130406023 2-330120130406023 2-3
30120130406023 2-3
IAEME Publication
 
Experimental Investigation and Parametric Studies of Surface Roughness Analy...
Experimental Investigation and Parametric Studies of Surface  Roughness Analy...Experimental Investigation and Parametric Studies of Surface  Roughness Analy...
Experimental Investigation and Parametric Studies of Surface Roughness Analy...
IJMER
 
Experimental Investigation and Parametric Studies of Surface Roughness Analys...
Experimental Investigation and Parametric Studies of Surface Roughness Analys...Experimental Investigation and Parametric Studies of Surface Roughness Analys...
Experimental Investigation and Parametric Studies of Surface Roughness Analys...
IJMER
 
3D Printable Concrete: Mixture Design, Simulation & Test Methods
3D Printable Concrete: Mixture Design, Simulation & Test Methods3D Printable Concrete: Mixture Design, Simulation & Test Methods
3D Printable Concrete: Mixture Design, Simulation & Test Methods
IRJET Journal
 
Optimization of Abrasive Water Jet of Drilling
Optimization of Abrasive Water Jet of DrillingOptimization of Abrasive Water Jet of Drilling
Optimization of Abrasive Water Jet of Drilling
ssuser0811ec
 
B7 PROGRESSSSSS [Autosaved] (1).pptx
B7 PROGRESSSSSS [Autosaved] (1).pptxB7 PROGRESSSSSS [Autosaved] (1).pptx
B7 PROGRESSSSSS [Autosaved] (1).pptx
ZoicGaming
 
A Review on Optimization of Cutting Parameters for Improvement of Surface Rou...
A Review on Optimization of Cutting Parameters for Improvement of Surface Rou...A Review on Optimization of Cutting Parameters for Improvement of Surface Rou...
A Review on Optimization of Cutting Parameters for Improvement of Surface Rou...
IRJET Journal
 
IRJET- Design of Spoon Mold using Flow Analysis and Higher End Design Software
IRJET- Design of Spoon Mold using Flow Analysis and Higher End Design SoftwareIRJET- Design of Spoon Mold using Flow Analysis and Higher End Design Software
IRJET- Design of Spoon Mold using Flow Analysis and Higher End Design Software
IRJET Journal
 

Similar to Batdwcwcdwcwcwcewcewcewxewecwcewcch-7.pptx (20)

A Review on Finite Element Analysis of Automobile roof header Manufactured By...
A Review on Finite Element Analysis of Automobile roof header Manufactured By...A Review on Finite Element Analysis of Automobile roof header Manufactured By...
A Review on Finite Element Analysis of Automobile roof header Manufactured By...
 
IRJET- Effect of Gasoline Exposure on the Mechanical Properties of PLA an...
IRJET-  	  Effect of Gasoline Exposure on the Mechanical Properties of PLA an...IRJET-  	  Effect of Gasoline Exposure on the Mechanical Properties of PLA an...
IRJET- Effect of Gasoline Exposure on the Mechanical Properties of PLA an...
 
Ijmer 46064551
Ijmer 46064551Ijmer 46064551
Ijmer 46064551
 
Optimization of Cutting Parameters Using Genetic Algorithm and Particle Swar...
Optimization of Cutting Parameters Using Genetic Algorithm  and Particle Swar...Optimization of Cutting Parameters Using Genetic Algorithm  and Particle Swar...
Optimization of Cutting Parameters Using Genetic Algorithm and Particle Swar...
 
1 i18 ijsrms0206178-v2-i6-prasad diwanji-30nov15
1 i18 ijsrms0206178-v2-i6-prasad diwanji-30nov151 i18 ijsrms0206178-v2-i6-prasad diwanji-30nov15
1 i18 ijsrms0206178-v2-i6-prasad diwanji-30nov15
 
CHARACTERIZATION AND ANALYSIS OF MECHANICAL PROPERTIES FOR 3D PRINTING MATERIALS
CHARACTERIZATION AND ANALYSIS OF MECHANICAL PROPERTIES FOR 3D PRINTING MATERIALSCHARACTERIZATION AND ANALYSIS OF MECHANICAL PROPERTIES FOR 3D PRINTING MATERIALS
CHARACTERIZATION AND ANALYSIS OF MECHANICAL PROPERTIES FOR 3D PRINTING MATERIALS
 
Experimental Studies on Effect of Layer Thickness on Surface Finish using FDM
Experimental Studies on Effect of Layer Thickness on Surface Finish using FDMExperimental Studies on Effect of Layer Thickness on Surface Finish using FDM
Experimental Studies on Effect of Layer Thickness on Surface Finish using FDM
 
Investigation of post processing techniques to reduce the surface roughness o...
Investigation of post processing techniques to reduce the surface roughness o...Investigation of post processing techniques to reduce the surface roughness o...
Investigation of post processing techniques to reduce the surface roughness o...
 
Investigation of post processing techniques to reduce the surface
Investigation of post processing techniques to reduce the surfaceInvestigation of post processing techniques to reduce the surface
Investigation of post processing techniques to reduce the surface
 
A Review: Fused Deposition Modeling – A Rapid Prototyping Process
A Review: Fused Deposition Modeling – A Rapid Prototyping ProcessA Review: Fused Deposition Modeling – A Rapid Prototyping Process
A Review: Fused Deposition Modeling – A Rapid Prototyping Process
 
Process parameter optimization of SLM process and application of Taguchi appr...
Process parameter optimization of SLM process and application of Taguchi appr...Process parameter optimization of SLM process and application of Taguchi appr...
Process parameter optimization of SLM process and application of Taguchi appr...
 
Manufacturing Process Simulation Based Geometrical Design for Complicated Parts
Manufacturing Process Simulation Based Geometrical Design for Complicated PartsManufacturing Process Simulation Based Geometrical Design for Complicated Parts
Manufacturing Process Simulation Based Geometrical Design for Complicated Parts
 
30120130406023 2-3
30120130406023 2-330120130406023 2-3
30120130406023 2-3
 
Experimental Investigation and Parametric Studies of Surface Roughness Analy...
Experimental Investigation and Parametric Studies of Surface  Roughness Analy...Experimental Investigation and Parametric Studies of Surface  Roughness Analy...
Experimental Investigation and Parametric Studies of Surface Roughness Analy...
 
Experimental Investigation and Parametric Studies of Surface Roughness Analys...
Experimental Investigation and Parametric Studies of Surface Roughness Analys...Experimental Investigation and Parametric Studies of Surface Roughness Analys...
Experimental Investigation and Parametric Studies of Surface Roughness Analys...
 
3D Printable Concrete: Mixture Design, Simulation & Test Methods
3D Printable Concrete: Mixture Design, Simulation & Test Methods3D Printable Concrete: Mixture Design, Simulation & Test Methods
3D Printable Concrete: Mixture Design, Simulation & Test Methods
 
Optimization of Abrasive Water Jet of Drilling
Optimization of Abrasive Water Jet of DrillingOptimization of Abrasive Water Jet of Drilling
Optimization of Abrasive Water Jet of Drilling
 
B7 PROGRESSSSSS [Autosaved] (1).pptx
B7 PROGRESSSSSS [Autosaved] (1).pptxB7 PROGRESSSSSS [Autosaved] (1).pptx
B7 PROGRESSSSSS [Autosaved] (1).pptx
 
A Review on Optimization of Cutting Parameters for Improvement of Surface Rou...
A Review on Optimization of Cutting Parameters for Improvement of Surface Rou...A Review on Optimization of Cutting Parameters for Improvement of Surface Rou...
A Review on Optimization of Cutting Parameters for Improvement of Surface Rou...
 
IRJET- Design of Spoon Mold using Flow Analysis and Higher End Design Software
IRJET- Design of Spoon Mold using Flow Analysis and Higher End Design SoftwareIRJET- Design of Spoon Mold using Flow Analysis and Higher End Design Software
IRJET- Design of Spoon Mold using Flow Analysis and Higher End Design Software
 

Recently uploaded

"Operational and Technical Overview of Electric Locomotives at the Kanpur Ele...
"Operational and Technical Overview of Electric Locomotives at the Kanpur Ele..."Operational and Technical Overview of Electric Locomotives at the Kanpur Ele...
"Operational and Technical Overview of Electric Locomotives at the Kanpur Ele...
nanduchaihan9
 
Adv. Digital Signal Processing LAB MANUAL.pdf
Adv. Digital Signal Processing LAB MANUAL.pdfAdv. Digital Signal Processing LAB MANUAL.pdf
Adv. Digital Signal Processing LAB MANUAL.pdf
T.D. Shashikala
 
Sustainable construction is the use of renewable and recyclable materials in ...
Sustainable construction is the use of renewable and recyclable materials in ...Sustainable construction is the use of renewable and recyclable materials in ...
Sustainable construction is the use of renewable and recyclable materials in ...
RohitGhulanavar2
 
Human_assault project using jetson nano new
Human_assault project using jetson nano newHuman_assault project using jetson nano new
Human_assault project using jetson nano new
frostflash010
 
DPWH - DEPARTMENT OF PUBLIC WORKS AND HIGHWAYS
DPWH - DEPARTMENT OF PUBLIC WORKS AND HIGHWAYSDPWH - DEPARTMENT OF PUBLIC WORKS AND HIGHWAYS
DPWH - DEPARTMENT OF PUBLIC WORKS AND HIGHWAYS
RyanMacayan
 
carpentry-11-module-1.docx 1 identifying tools
carpentry-11-module-1.docx 1 identifying toolscarpentry-11-module-1.docx 1 identifying tools
carpentry-11-module-1.docx 1 identifying tools
ChristopherAltizen2
 
Red Hat Enterprise Linux Administration 9.0 RH124 pdf
Red Hat Enterprise Linux Administration 9.0 RH124 pdfRed Hat Enterprise Linux Administration 9.0 RH124 pdf
Red Hat Enterprise Linux Administration 9.0 RH124 pdf
mdfkobir
 
AI chapter1 introduction to artificial intelligence
AI chapter1 introduction to artificial intelligenceAI chapter1 introduction to artificial intelligence
AI chapter1 introduction to artificial intelligence
GeethaAL
 
III B.TECH CSE_flutter Lab manual (1).docx
III B.TECH CSE_flutter Lab manual (1).docxIII B.TECH CSE_flutter Lab manual (1).docx
III B.TECH CSE_flutter Lab manual (1).docx
divijareddy0502
 
Digital Image Processing - Module 4 Chapter 2
Digital Image Processing - Module 4 Chapter 2Digital Image Processing - Module 4 Chapter 2
Digital Image Processing - Module 4 Chapter 2
821priyankaj
 
Machine Learning- Perceptron_Backpropogation_Module 3.pdf
Machine Learning- Perceptron_Backpropogation_Module 3.pdfMachine Learning- Perceptron_Backpropogation_Module 3.pdf
Machine Learning- Perceptron_Backpropogation_Module 3.pdf
Dr. Shivashankar
 
Agricultural Profitability through Resilience: Smallholder Farmers' Strategie...
Agricultural Profitability through Resilience: Smallholder Farmers' Strategie...Agricultural Profitability through Resilience: Smallholder Farmers' Strategie...
Agricultural Profitability through Resilience: Smallholder Farmers' Strategie...
IJAEMSJORNAL
 
If we're running two pumps, why aren't we getting twice as much flow? v.17
If we're running two pumps, why aren't we getting twice as much flow? v.17If we're running two pumps, why aren't we getting twice as much flow? v.17
If we're running two pumps, why aren't we getting twice as much flow? v.17
Brian Gongol
 
Indian Railway Signalling concepts and basics.pdf
Indian Railway Signalling concepts and basics.pdfIndian Railway Signalling concepts and basics.pdf
Indian Railway Signalling concepts and basics.pdf
princeshah76
 
Developing a Genetic Algorithm Based Daily Calorie Recommendation System for ...
Developing a Genetic Algorithm Based Daily Calorie Recommendation System for ...Developing a Genetic Algorithm Based Daily Calorie Recommendation System for ...
Developing a Genetic Algorithm Based Daily Calorie Recommendation System for ...
AIRCC Publishing Corporation
 
charting the development of the autonomous train
charting the development of the autonomous traincharting the development of the autonomous train
charting the development of the autonomous train
huseindihon
 
Generative AI and Large Language Models (LLMs)
Generative AI and Large Language Models (LLMs)Generative AI and Large Language Models (LLMs)
Generative AI and Large Language Models (LLMs)
rkpv2002
 
Safety Operating Procedure for Testing Lifting Tackles
Safety Operating Procedure for Testing Lifting TacklesSafety Operating Procedure for Testing Lifting Tackles
Safety Operating Procedure for Testing Lifting Tackles
ssuserfcf701
 
Protect YugabyteDB with Hashicorp Vault.pdf
Protect YugabyteDB with Hashicorp Vault.pdfProtect YugabyteDB with Hashicorp Vault.pdf
Protect YugabyteDB with Hashicorp Vault.pdf
Gwenn Etourneau
 
Updated Limitations of Simplified Methods for Evaluating the Potential for Li...
Updated Limitations of Simplified Methods for Evaluating the Potential for Li...Updated Limitations of Simplified Methods for Evaluating the Potential for Li...
Updated Limitations of Simplified Methods for Evaluating the Potential for Li...
Robert Pyke
 

Recently uploaded (20)

"Operational and Technical Overview of Electric Locomotives at the Kanpur Ele...
"Operational and Technical Overview of Electric Locomotives at the Kanpur Ele..."Operational and Technical Overview of Electric Locomotives at the Kanpur Ele...
"Operational and Technical Overview of Electric Locomotives at the Kanpur Ele...
 
Adv. Digital Signal Processing LAB MANUAL.pdf
Adv. Digital Signal Processing LAB MANUAL.pdfAdv. Digital Signal Processing LAB MANUAL.pdf
Adv. Digital Signal Processing LAB MANUAL.pdf
 
Sustainable construction is the use of renewable and recyclable materials in ...
Sustainable construction is the use of renewable and recyclable materials in ...Sustainable construction is the use of renewable and recyclable materials in ...
Sustainable construction is the use of renewable and recyclable materials in ...
 
Human_assault project using jetson nano new
Human_assault project using jetson nano newHuman_assault project using jetson nano new
Human_assault project using jetson nano new
 
DPWH - DEPARTMENT OF PUBLIC WORKS AND HIGHWAYS
DPWH - DEPARTMENT OF PUBLIC WORKS AND HIGHWAYSDPWH - DEPARTMENT OF PUBLIC WORKS AND HIGHWAYS
DPWH - DEPARTMENT OF PUBLIC WORKS AND HIGHWAYS
 
carpentry-11-module-1.docx 1 identifying tools
carpentry-11-module-1.docx 1 identifying toolscarpentry-11-module-1.docx 1 identifying tools
carpentry-11-module-1.docx 1 identifying tools
 
Red Hat Enterprise Linux Administration 9.0 RH124 pdf
Red Hat Enterprise Linux Administration 9.0 RH124 pdfRed Hat Enterprise Linux Administration 9.0 RH124 pdf
Red Hat Enterprise Linux Administration 9.0 RH124 pdf
 
AI chapter1 introduction to artificial intelligence
AI chapter1 introduction to artificial intelligenceAI chapter1 introduction to artificial intelligence
AI chapter1 introduction to artificial intelligence
 
III B.TECH CSE_flutter Lab manual (1).docx
III B.TECH CSE_flutter Lab manual (1).docxIII B.TECH CSE_flutter Lab manual (1).docx
III B.TECH CSE_flutter Lab manual (1).docx
 
Digital Image Processing - Module 4 Chapter 2
Digital Image Processing - Module 4 Chapter 2Digital Image Processing - Module 4 Chapter 2
Digital Image Processing - Module 4 Chapter 2
 
Machine Learning- Perceptron_Backpropogation_Module 3.pdf
Machine Learning- Perceptron_Backpropogation_Module 3.pdfMachine Learning- Perceptron_Backpropogation_Module 3.pdf
Machine Learning- Perceptron_Backpropogation_Module 3.pdf
 
Agricultural Profitability through Resilience: Smallholder Farmers' Strategie...
Agricultural Profitability through Resilience: Smallholder Farmers' Strategie...Agricultural Profitability through Resilience: Smallholder Farmers' Strategie...
Agricultural Profitability through Resilience: Smallholder Farmers' Strategie...
 
If we're running two pumps, why aren't we getting twice as much flow? v.17
If we're running two pumps, why aren't we getting twice as much flow? v.17If we're running two pumps, why aren't we getting twice as much flow? v.17
If we're running two pumps, why aren't we getting twice as much flow? v.17
 
Indian Railway Signalling concepts and basics.pdf
Indian Railway Signalling concepts and basics.pdfIndian Railway Signalling concepts and basics.pdf
Indian Railway Signalling concepts and basics.pdf
 
Developing a Genetic Algorithm Based Daily Calorie Recommendation System for ...
Developing a Genetic Algorithm Based Daily Calorie Recommendation System for ...Developing a Genetic Algorithm Based Daily Calorie Recommendation System for ...
Developing a Genetic Algorithm Based Daily Calorie Recommendation System for ...
 
charting the development of the autonomous train
charting the development of the autonomous traincharting the development of the autonomous train
charting the development of the autonomous train
 
Generative AI and Large Language Models (LLMs)
Generative AI and Large Language Models (LLMs)Generative AI and Large Language Models (LLMs)
Generative AI and Large Language Models (LLMs)
 
Safety Operating Procedure for Testing Lifting Tackles
Safety Operating Procedure for Testing Lifting TacklesSafety Operating Procedure for Testing Lifting Tackles
Safety Operating Procedure for Testing Lifting Tackles
 
Protect YugabyteDB with Hashicorp Vault.pdf
Protect YugabyteDB with Hashicorp Vault.pdfProtect YugabyteDB with Hashicorp Vault.pdf
Protect YugabyteDB with Hashicorp Vault.pdf
 
Updated Limitations of Simplified Methods for Evaluating the Potential for Li...
Updated Limitations of Simplified Methods for Evaluating the Potential for Li...Updated Limitations of Simplified Methods for Evaluating the Potential for Li...
Updated Limitations of Simplified Methods for Evaluating the Potential for Li...
 

Batdwcwcdwcwcwcewcewcewxewecwcewcch-7.pptx

  • 1. Department of Mechanical Engineering Academic Year: 2023-24 OPTIMIZATION OF PRINTING PARAMETERS IN FUSED DEPOSITION MODELLING FOR IMPROVING PART QUALITY AND MECHANICAL STRENGTH 21P35A0312 - M.V.K.RAHUL 20P31A0317 - C.ASHISH RAM 20P31A0332 - K.N.S.M.KIRAN 20P31A0333 - K.SRINIVAS Under the Guidance of Dr.CH.V.V.M.J.SATISH Associate Professor M.Tech, Phd BATCH – 07:
  • 2. Contents • Abstract • Literature Review • Introduction • Estimated CO-PO mapping • Plan of Action • Cost estimation Report • Project Overview • Methodology and Experimentation • Results • Conclusion • References 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 2
  • 3. Abstract This project seeks to optimize printing parameters in Fused Deposition Modeling (FDM) to enhance part quality and improve the mechanical strength of the printed part. FDM is a widely adopted 3D printing technology, and improving its efficiency is crucial for advancing additive manufacturing. The project aims to systematically investigate various printing parameters and their interactions to find an optimal configuration that balances part quality, production time, and mechanical strength. Through experimental research and analysis, the project aims to provide valuable insights and guidelines for users aiming to maximize the benefits of FDM technology, with a focus on fast and quality prototype production. We are aiming to build a low cost 3d printer by purchasing various parts and assembling them to perform our experimentation. By using CAD design and Slicing software, we are going to vary the various process parameters like layer height, extrusion temperature etc., and perform Design of Experiments(Taguchi Approach) to find the optimal parameters suitable for our 3d printer built in order to obtain good surface finish and improved mechanical strength of the printed parts. 5/14/2024 3 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY
  • 4. Introduction 5/14/2024 4 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY Additive manufacturing (AM), commonly known as 3D printing, is the process of creating parts by accumulating material layer upon layer, starting directly from a computer-aided design model. There are many prominent advantages of AM that can be listed out, such as direct manufacturing process without molds, unrestricted to the complexity of product structure, unlimited in innovative and creative design, high utilization of material and eco-friendly. Nowadays, the use of 3D printing is increasingly popular not only in prototype phase but also in finished product, in various fields from aerospace, automotive to medical. Parallel to the rapid increase of 3D printing use, it is essential to have an instruction for the optimal process parameters to attain qualified products regards to efficiency. In addition, due to the principle of 3D printing is adding layer by layer material in order to make a finished part, product mechanical property is the important quality criteria should be considered.
  • 5. Thus, investigating the effect of each process parameters on mechanical characteristics of the FDM parts helps to adjust level of process variables leading to improvement in quality of parts. There are various factors such as orientation angle, raster angle, layer thickness, shell thickness, infill pattern, infill density, extrusion temperature, printing speed which affect the ultimate tensile strength and surface finish for finished product. The levels of these process parameters can be varied using a slicing software and by finding the optimal levels of these process parameters, the response output variables which are the mechanical properties of the printed parts can be optimized. 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 5
  • 6. Literature In the past several years, researchers have examined the outcomes of 3D printing parameters on key metrics of FDM to improve the condition of the part by maximizing yield strength and ultimate tensile strength, among other mechanical properties. 1. Hassanifard and Hashemi [1] studied the effect of part’s build orientation and raster angle on the strain-life fatigue of specimens made of Ultem 9085, polycarbonate (PC), and polylactic acid (PLA). Parts were created based on ASTM D638-14 and ASTM D790-17 standards. The authors concluded that infill density affected the mechanical properties of the printed part. 2. The aim of the work reported by Verbeeten et al. [2] was to investigate the strain-rate dependence of the yield stress for tensile samples made of PLA, based on ISO 527-2 standard. Printing speed, infill orientation angle, and bed temperature were modified. One of the conclusions of the study was that a change of infill orientation angle from 0 to 90° provided anisotropic effects to the pieces. 5/14/2024 6 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY
  • 7. 3. Zhao et al. [3] explored the effect of printing angle and layer thickness on the mechanical properties of specimens made of PLA. The standard used to fabricate the units was ISO 527-2- 2012. Tensile strength increased with higher values of printing angle and reduced ones of layer thickness. 4. Tanoto et al. [4] evaluated dimensional accuracy, processing time, and tensile strength of 3D printed components. The components were made of ABS, using FDM technology. The printing plane and the orientation angle were selected as the response variables to be analyzed. The specimens employed in the experimental trials belong to type IV, according to the ASTM D638- 02 standard. Printing time diminished when the part was oriented in the XZ plane at 90°. This orientation also provided a specimen’s length value closer to the one of the ASTM standard. 5. The work of Alafaghani et al. [5] presented an experiment to determine the values of infill rate, infill pattern, the orientation of the part, and layer thickness that enhanced dimensional accuracy and mechanical properties of specimens made of PLA. The part design followed type IV specifications according to the ASTM D638-15 standard. Lower values of fill density and shell thickness and higher values of layer thickness and feed rate reduced the measured values. 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 7
  • 8. 6. Huynh et al. [6] considered the effect of infill rate, infill pattern, and layer thickness on the dimensional precision of parts made of PLA using FDM. The piece was a CAD model created by the authors, and an orthogonal array L27 was applied, along with a fuzzy approach to optimize printing parameters. 7. The work of Padhi et al. [7] shows a comparison between the dimensional deviation of printed specimens from the dimensions of a CAD model. An L27 orthogonal array allowed to modify the infill angle, raster width, air gap, orientation of the part, and layer thickness. The material of the specimens is ABS P400. A medium value for layer thickness and raster width, the greatest one for the air gap and the least for orientation and raster angle, granted the highest dimensional precision. 8. Mohamed et al. [8] investigated the dimensional accuracy of specimens made of a PCABS blend, employing FDM. The process parameters that were modified are raster angle, raster width, air gap, part orientation, layer thickness, and the number of contours. The geometry of the specimens is according to the standards ASTM D5418-07 and ASTM D7028-07e1. The layer thickness was the factor that affected all the responses. 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 8
  • 9. Estimated CO-PO Mapping PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO1 0 PSO 1 PSO 2 Pso2 CO1 3 2 3 2 CO2 3 3 2 3 2 CO3 3 1 2 2 3 3 2 C04 3 3 3 2 3 1 1 C05 3 2 3 2 3 1 2 3 2 C06 3 3 3 2 3 3 3 5/14/2024 9 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY
  • 10. Plan of Action 5/14/2024 10 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY Sl. No Date/Duration Description 1 Week-1 18-01-24 to 24-01-24 Define Project Scope and Objectives: Clearly outline the project's goals, including the specific printing parameters to be optimized, cost considerations, etc., 2 Week-2 25-01-24 to 31-01-24 Cost Estimation and Budgeting: Develop a detailed cost estimation for the project, considering expenses related to materials, equipment and other relevant factors. 3 Week-3 01-02-24 to 07-02-24 Review Existing Literature: Conduct an in-depth review of relevant literature to understand about our project goals 4 Week-4 08-02-24 to 14-02-24 Learn basic Designing for 3d printing: Learn and practice designing simple 2d and 3d figures like cubes and cylinders in ONSHAPE
  • 11. Sl. No Date/Duration Description 5 Week-5 15-02-24 to 21-02-24 Learn basics in Slicing Software: Learn and Practice to use Ulti maker Cura Slicing software and about the various parameters that can be controlled for 3d printing 6 Week-6 22-02-24 to 28-02-24 Learn about Design of Experiments(DOE): Study about the Design of Experiments(DOE) and Taguchi Approach and practice using it in Minitab 7 Week-7 29-02-24 to 06-03-24 Purchase and Assemble the 3d Printer: Purchase various parts and components and assemble them to build our 3d printer 8 Week- 8 07-03-24 to 13-03-24 Practice printing on the 3d printer: Practice designing and give sample prints in our 3d printer 9 Week- 9 14-03-24 to 20-03-24 Designing a standard specimen for experimentation: Designing a standard test specimen for experimentation 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 11
  • 12. Sl. No Date/Duration Description 10 Week- 10 21-03-24 to 27-03-24 Printing the test specimens : Printing all the required test specimens with varying parameters on the 3d printer 11 Week- 11 28-03-24 to 03-04-24 Surface Roughness testing of printed parts: Testing and obtaining required values of surface roughness for the printed parts with Surface roughness testing machine 12 Week- 12 04-04-24 to 10-04-24 Ultimate Tensile strength testing of printed parts: Testing the printed parts in UTM for obtaining the strength values of all printed parts 13 Week- 13 11-04-24 to 17-04-24 Analysis of the results with Taguchi Approach: Analysis and application of Taguchi Statistical Approach to obtain optimal parameters 14 Week- 14 18-04-24 to 24-04-24 Verification and Document preparation: Verification of the end results and document preparation for the project 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 12
  • 13. Budget estimation Sl. No Equipment/Parts Quantity Price per Quantity Total Price in INR 1 Print material 1 800 800 2 Nozzle Set 1 600 600 3 Stepper Motors 3 700 2100 4 Controller Board 1 700 700 5 Frame 1 3000 3000 6 Motion Components 1 1200 1200 7 Power supply unit 1 1000 1000 8 Print Bed 1 400 400 9 Extruder 1 5500 5500 10 Feeder System 1 1500 1500 5/14/2024 13 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY Total Budget Estimation = Rs.17000
  • 14. Project Overview 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 14 PARAMETER OPTIMIZATION IN FUSED DEPOSITION MODELLING: In order to find the optimal levels of parameters for our assembled Any Cubic Kobra 2 Neo 3D Printer for obtaining high mechanical strength and good surface finish, we have considered 3 factors which are majorly influencing the mechanical properties i.e., strength and surface roughness of the 3d printed parts. The 3 factors are layer height, infill percent and extrusion temperature. From the previous studies done by different researchers, layer height is the main influencing factor behind the surface roughness of the 3d printed parts and the factors layer height and infill percent and extrusion temperature influence the strength of the printed parts.
  • 15. • Layer Height: • The thickness of each layer of deposited material is called the ‘layer height’. • The surface quality of the finished part is proportional to how small the layer height is; smaller layer heights result in smother surface finishes. • For FDM printers, the number of layers is one indicator of how much time a 3D print will take. Choosing a smaller layer height will divide a 3D model into more layers, increasing the print time. For Any Cubic Kobra 2 Neo 3D Printer, the recommended layer height in Cura is 0.2mm. And Our nozzle diameter is 0.4mm. So, we have taken 3 levels of layer height from 0.2-0.3 mm. Layer height : Level-1 : 0.20mm Level-2 : 0.25mm Level-3 : 0.30mm 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 15
  • 16. • Infill Density: • Infill density is the “fullness” of the inside of a part. In slicers, this is usually defined as a percentage between 0 and 100. Infill Density : Level-1 : 15% Level-2 : 60% Level-3 : 100% • Extrusion Temperature: • Extrusion temperature is the temperature the extruder heats to during your print. • PLA melts at extrusion temperatures from about 180°C.The suggested temperature is 200 °C and the Maximum temperature the printer can attain is 260 °C Extrusion Temperature : Level-1 : 200 °C Level-2 : 230 °C Level-3 : 260 °C 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 16
  • 17. Design Matrix for Experimentation 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 17 S. No. FACTORS LEVEL 1 LEVEL 2 LEVEL 3 1 LAYER HEIGHT 0.1 0.25 0.3 2 INFILL PERCENTAGE 15 60 100 3 EXTRUSION TEMPERATURE 200 230 260
  • 18. Taguchi Statistical design in Minitab Runs. A B C 1. 1 1 1 2. 1 2 2 3. 1 3 3 4. 2 1 2 5. 2 2 3 6. 2 3 1 7. 3 1 3 8. 3 2 1 9. 3 3 2 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 18 To find the optimal levels of the printing parameters i.e., layer height, infill percent and extrusion temperature, we are considered 3 levels for each factor following low, medium and high levels of the respective printing parameters as per the specifications of the 3d printer. We used Design of Experiments (D.O.E) for finding the optimal parameter levels. In D.O.E, we followed L9 Orthogonal Array from Taguchi Design Approach and with the help of Mini Tab Statistical Software, we found out the optimal levels of the considered three factors. Taguchi Design: L9 Orthogonal Array for 3 factors with 3 levels: In this design, Factor A is Layer Height with 3 different levels 1,2,3.Factor B is Infill Percent with 3 different levels 1,2,3.Factor C is Extrusion Temperature with three different levels 1,2,3 columns of L9 (3^4) array: 1 2 3
  • 19. L9 0rthogonal Array (3 factors, 3 levels) Runs Layer Height (mm) Infill Density (%) Extrusion Temperature (°C) 1 0.20 15 200 2 0.20 60 230 3 0.20 100 260 4 0.25 15 230 5 0.25 60 260 6 0.25 100 200 7 0.30 15 260 8 0.30 60 200 9 0.30 100 230 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 19
  • 20. Methodology and Experimentation • Sample preparation • The specimens used in this study to evaluate the mechanical properties are modelled based on American Society for Testing and Materials ASTM D638 type I standards for plastic tensile testing. All the specimens were printed using PLA filaments and a Any Cubic Kobra 2 Neo 3D Printer. ASTM D638 type I 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 20
  • 21. • Designing and Slicing: • We designed the specimen in ONSHAPE CAD Software as per its standard dimensions and sliced it in UltiMaker CURA Slicing software by varying the levels of parameters i.e., layer height, infill density and extrusion temperature each time as per the Taguchi L9 Orthogonal Design Approach. • We made 9 G-codes for 9 experimental runs and printed the sample specimens. slicing of ASTM D638 type-I in UltiMaker Cura 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 21
  • 22. • 3D Printing of the Specimens 3d printed specimens assembled 3d printer 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 22
  • 23. • Tensile test on Universal Testing Machine(UTM) UTM tensile testing of specimen on UTM 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 23
  • 24. Experimental Results of Tensile Test Runs Layer Height (mm) Infill Density (%) Extrusion Temperature (°C) Printing Time (min) Ultimate Tensile Strength (Mpa) 1 0.20 15 200 57 133.173 2 0.20 60 230 61 135.096 3 0.20 100 260 64 140.865 4 0.25 15 230 51 133.653 5 0.25 60 260 53 136.538 6 0.25 100 200 56 141.827 7 0.30 15 260 46 133.659 8 0.30 60 200 46 138.942 9 0.30 100 230 49 139.909 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 24
  • 25. • Surface Roughness Test using Surface Roughness Tester MEXTECH SRT-6200 Surface Roughness Measuring Ra for a specimen Tester 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 25
  • 26. Experimental Results of Surface Roughness Test Runs Layer Height (mm) Infill Density (%) Extrusion Temperature (°C) Printing Time (min) Surface Roughness – Ra (microns) 1 0.20 15 200 57 10.230 2 0.20 60 230 61 9.456 3 0.20 100 260 64 5.354 4 0.25 15 230 51 10.390 5 0.25 60 260 53 9.027 6 0.25 100 200 56 10.780 7 0.30 15 260 46 7.971 8 0.30 60 200 46 9.758 9 0.30 100 230 49 5.939 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 26
  • 27. Results • Taguchi Analysis: Ultimate Tensile Strength (MPa) versus Layer Height (mm), Infill Percent (%), Extrusion Temperature(0C) • Optimal Levels for Layer Height – 0.30mm, Infill Percent – 100%, Extrusion Temperature - 2000C for improved mechanical strength. 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 27
  • 28. • Taguchi Analysis: Surface Roughness Ra (microns) versus Layer Height (mm), Infill Percent (%), Extrusion Temperature(0C) • Optimal Levels for Layer Height – 0.25mm, Infill Percent – 15%, Extrusion Temperature - 2000C for improved Surface Quality. 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 28
  • 29. • Taguchi Analysis: Ultimate Tensile Strength (MPa), Average Surface Roughness Ra (microns) versus Layer Height (mm), Infill Percent (%), Extrusion Temperature(0C) • Optimal Levels for Layer Height – 0.25mm, Infill Percent – 100%, Extrusion Temperature - 2000C for nominal values of Surface Quality and Strength. 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 29
  • 30. Conclusion The conclusions of our Project Work “Optimization of 3D Printing Parameters for improving Surface Quality and Mechanical Strength” are as follows: 1. For obtaining Printed parts with high mechanical strength, the optimal levels of the process parameters were found out as: Layer height: 0.3 mm; Infill Percent : 100% ; Extrusion Temperature : 2000C and Infill Density is the process parameter which has more influence on the Mechanical Strength of the printed parts. 2. For obtaining Printed parts with good surface quality i.e., lower values of Surface Roughness, the optimal levels of the process parameters were found out as: Layer height: 0.25 mm; Infill Percent : 15% ; Extrusion Temperature : 2000C and Extrusion Temperature is the process parameter which has more influence on the Surface Quality of the printed parts. 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 30
  • 31. 3. For obtaining printed parts with nominal values of strength and surface roughness i.e., average values of strength and surface roughness, the optimal levels of the processing parameters are: Layer height: 0.25 mm; Infill Percent : 100% ; Extrusion Temperature : 2000C and Infill Density is the process parameter which influences both Strength and Surface Quality of the printed parts. Through this research work, we would suggest a Full Factorial DOE Statistical Approach for well prediction of the response for future work. For a Full Factorial DOE, experimenting with 3 factors with 3 levels each would require 27 experimental runs which would consume more material and power but it would give more accurate results than the Taguchi Methodology as here we only did 9 experimental runs for 3 factors with 3 levels each. It is also suggested to develop a Regression Model following the Full factorial DOE method to predict the Strength and Surface Roughness of the printed parts mathematically.Also, a smaller range of Layer Height (<0.20mm) should be addressed and investigated. This research also suggests that effectiveness of orientation angle and the effect of Printing Speed should be included in the future research. 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 31
  • 32. References [1] Hassanifard S, Hashemi SM (2020) On the strain-life fatigue parameters of additive manufactured plastic materials through fused filament fabrication process. Additive Manufacturing 32:100973. https://doi. org/10.1016/j.addma.2019.100973 [2] Verbeeten WMH, Lorenzo-Bañuelos M, Arribas-Subiñas PJ (2020) Anisotropic ratedependent mechanical behaviour of poly lactic acid (PLA) processed by material extrusion. Additive Manufacturing 31:100968. https://doi.org/10.1016/j.addma.2019.100968 [3] Zhao Y, Chen Y, Zhou Y (2019) Novel mechanical models of tensile strength and elastic property of FDM AM PLA materials: experimental and theoretical analyses. Mater Des 181:108089. https:// doi.org/10.1016/j.matdes.2019.108089 [4] Tanoto YY, Anggono J, Siahaan IH, Budiman W (2017) The effect of orientation difference infused deposition modeling of ABS polymer on the processing time, dimension accuracy, and strength. in: AIP Conference Proceedings. https://doi.org/10.1063/1.4968304 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 32
  • 33. [5] Alafaghani A, Qattawi A, Alrawi B, Guzman A (2017) Experimental optimization of fused deposition modelling processing parameters: a design-for- manufacturing approach. Procedia Manufacturing 10:791–803. https://doi.org/10.1016/j.promfg.2017.07.079 [6] Huynh HN, Nguyen AT, Ha NL, Ha Thai TT (2017) Application of fuzzy Taguchi method to improve the dimensional accuracy of fused deposition modelling processed product. In: Proceedings 2017 International Conference on System Science and Engineering, ICSSE 2017. https://doi.org/10.1109/ICSSE.2017. 8030847 [7] Padhi SK, Sahu RK, Mahapatra SS, Das HC, Sood AK, Patro B, Mondal AK (2017) Optimization of fused deposition modelling process parameters using a fuzzy inference system coupled with Taguchi philosophy. Additive Manufacturing 5:231–242. https://doi.org/10.1007/s40436-017-0187-4 [8] Mohamed OA, Masood SH, Bhowmik JL (2016) Optimization of fused deposition modelling process parameters for dimensional accuracy using I- optimality criterion. Meas J Int Meas Confed 81: 174–196. https://doi.org/10.1016/j.measurement.2015.12.011 5/14/2024 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY 33
  • 34. 5/14/2024 34 ADITYA COLLEGE OF ENGINEERING & TECHNOLOGY