1. INTERNATIONAL Mechanical Engineering and Technology (IJMET),
ISSN 0976 International Journal of JOURNAL OF MECHANICAL
ENGINEERING 6340(Print), ISSN 0976 AND TECHNOLOGYSep- Dec (2012)
IAEME 6359(Online) Volume 3, Issue 3, (IJMET)ISSN 0976 6340
(Print)ISSN 0976 6359 (Online) IJMETVolume 3, Issue 3, September -
December (2012), pp. 531-544 IAEME: www.iaeme.com/ijmet.aspJournal
Impact Factor (2012): 3.8071 (Calculated by GISI)
IAEMEwww.jifactor.com INVESTIGATION OF POST PROCESSING TECHNIQUES
TO REDUCE THE SURFACE ROUGHNESS OF FUSED DEPOSITION MODELED PARTS
Addanki Sambasiva Rao1*, Medha A Dharap2, J V L Venkatesh3, Deepesh
Ojha4 1 Assistant Professor, Department of Mechanical Engineering,
Veermata Jijabai Technological Institute, Mumbai, India. Email:
[email protected] 2 Professor, Department of Mechanical
Engineering, Veermata Jijabai Technological Institute, Mumbai,
India. Email: [email protected] 3 Associate Professor,
Production Engineering Department, SGGSIE&T, Nanded,
Maharashtra, India. Email: [email protected] 4 PG Student,
Department of Mechanical Engineering, Veermata Jijabai
Technological Institute, Mumbai, India. Email:
[email protected] ABSTRACT Fused Deposition Modeling is most
popular rapid prototyping process because of its faster, economical
and clean technology, however it suffers from low surface finish
quality. To improve its surface finish quality, various attempts
had been made by several researchers by controlling various process
parameters. The main objective of this research is to apply
chemical treatment processes through Design of Experiments using
different chemicals with variant conditions like different levels
of concentration, time of exposure, temperatures and initial
roughness, interaction effects of the process parameters have also
been analyzed. ANOVA technique is used to find out the significant
factors affecting the surface finish. Results show satisfactory
improvement in surface finish of FDM parts (ABS) with simple
inexpensive and harmless chemical treatment processes. Keywords :
Acrylonitrile Butadiene Styrene (ABS), ANOVA, Chemical Treatment,
Design of Experiments, Fused Deposition Modeling, Post-Processing,
Surface Roughness. I. INTRODUCTION Rapid prototyping (RP)
technologies provide the ability to fabricate initial prototypes
from various model materials. Stratasyss Fused Deposition Modeling
(FDM) is a typical RP process that can fabricate prototypes out of
ABS plastic [1]. FDM rapid prototyping process is quite popular in
industry for various reasons such as: different raw materials
(thermo plastics) can be used as long as the appropriate hot head
is available; FDM parts are very strong and hence can work as
functional parts; it does not employ lasers, hence is less 531
2. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEMEexpensive and there are no
safety related issues; It does not use liquid/powder raw
materialsand hence is a clean process; It can be kept in an office
environment as a 3D printer; veryeasy to remove the support
material; this is probably the easiest of all RP processes; this
isthe cheapest technology; etc. Parts produced by FDM are, however,
less accurate than those produced by otherrapid prototyping
processes such as Stereo lithography Apparatus (SLA), Solid
GroundCuring (SGC). Besides, FDM process is very slow as every
point of the volume is addressedby a mechanical device. The key
issue with FDM process is surface roughness because of itsstaircase
effect (the angle between the vertical axis and surface tangents)
[2]. The poorsurface finish affects the functioning of RP parts,
depending on the geometry of the enclosingsurface, the building
strategy, layer thickness and orientation of the part; this
drawback mayoutweigh the advantages of RP parts [3]. In literature,
several researchers have proposed various methods to reduce the
surfaceroughness of the FDM parts of ABS material. One of the
prominent methods is to control theprocess parameters like layer
thickness, build orientation, raster width, raster angle, air
gapetc.. In this method process parameters were optimized using
statistical techniques like designof experiments and gray
relational analysis have been integrated for obtaining the
optimumprocess parameter values [3]. The process parameters
influence the responses in a highly non-linear manner; therefore,
prediction of overall dimensional accuracy is made based
onartificial neural network (ANN) [4]. Several algorithms were also
developed to obtainoptimum part deposition orientation for fused
deposition modeling process for enhancing partsurface finish and
reducing build time [5, 6]. Another method is adaptive slicing
scheme in which slices of different thicknesses indifferent zones
are produced while building the part [7-10]. Daekeon Ahn et al
investigatedthe relation between surface roughness and overlap
interval [11], they also analyzed anddiscussed the effects of
surface angle and filament section shape to the surface
roughness.Debapriya Chakraborty et al introduced a new kind of
deposition method called Curved layerFDM or CLFDM which offers
solution to the issues of surface roughness and strength forthin
curved shell-type parts, this process proposes an entirely new
building paradigm forFDM, the filaments would be deposited along
curved (essentially non horizontal) pathsinstead of planar
(horizontal) paths [12]. A mathematical technique has been
developed byW. Rattanawong et al to determine best part orientation
based on minimum volume error(VE) in the part due to staircase
effect [13]. Noshir A. Langrana et al have developed amethod to
fabricate the highest quality of multi-material parts. In this
method, a virtualsimulation system and experimental real time video
microscopy have been developed. In thisvirtual simulation, one can
check or test a variety of the layered manufacturing
processparameters, and make the best selection of tool path and
other parameters to obtain highquality parts [14] One more method
for improving surface finish is chemical treatment method which
hasbeen proposed by L.M. Galantucci et al [2]. In this chemical
treatment method,Dimethylketone (Acetone) with 90% concentrated
solution and 10% water was used andparts were immersed in diluted
solution for 5 minutes and also suggested that further studiesneed
to be conducted on freeform products, also using other
dimethylketone solvents such asethylene and using designed
experiments to optimize the process in terms of the
solutionconcentration and process time. To the best of the authors
knowledge, no investigations ofchemical treatment method have been
reported since the work of L.M. Galantucci et al. andhence the
present study has been undertaken by the authors to investigate the
optimumconditions for obtaining best surface finish from the
chemical treatment process. 532
3. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEMEII. PROBLEM DEFINITION L.M.
Galantucci et al [2] had proposed a method of chemical treatment of
ABS(Acrylonitrile Butadiene Styrene) parts which yields a
significant improvement of the surfacefinish of the treated
specimens. The chemical treatment method is economical, fast and
easyto use. However chemical treatment method has not been analyzed
considering differenttypes of chemicals, different concentration
levels of chemicals, effect of elevatedtemperatures, different
initial roughness of the parts, time of exposure along with
theunderlying interaction effects for obtaining optimum surface
finish. This paper reports designof experiments for analyzing
chemical post processing treatment method to identify
maincontrolling factors, side effects of the process parameter
settings and disturbances to theprocess for ABS
plastics.III.METHODOLOGY In this paper we will be optimizing the
chemical treatment process using Design ofExperiments (DOE). The
factors affecting the chemical treatment process were identified
byperforming numerous trials, based on these trials concentration,
temperature, time ofexposure and initial roughness were identified
as possible main factors. These are analyzedusing Design of
Experiments (DOE). DOE is done for two different chemicals
i.e.Dimethylketone (Acetone) and Methylethylketone (MEK), test
specimen selected are shownin Fig.1(a) to Fig.1(e)... The
optimization method is based on Design of Experiments (DOE)and
Analysis of Variance (ANOVA). It identifies significant parameters
affecting the surfacefinish, to which more attention must be paid
in order to attain best possible results.3.1 Statistical Design Of
Experiments Statistical DOE refers to the process of planning the
experiment so that appropriate datathat can be analyzed by
statistical methods will be collected, resulting in valid and
objectiveconclusions [15,16]. A statistical tool is always
preferred for drawing the meaningfulconclusion from a experimental
design data. There are two aspects to any experimentalproblem; the
design of the experiment and the statistical analysis of the data.
When manyfactors control the performance of any system then it is
essential to find out significantfactors which need special
attention either to control or optimize the system
performance.Taguchis concept of Orthogonal Array (OA) as a part of
Statistical DOE is used in suchsituations to plan the set of
experiments and ANOVA technique is used to find out thesignificant
factors. These techniques have been used in the current study to
investigate significant factorsaffecting the surface roughness of
FDM parts (ABS P400) out of concentration of solution C,temperature
of the chemical bath Tp, initial roughness of parts Ri and Time for
which theparts are treated Tm. The first step in constructing an
orthogonal array to fit a specific casestudy is to count the total
degrees of freedom that tell the minimum number of experimentsthat
must be performed to study all the chosen control factors. The
number of degrees offreedom associated with a factor is equal to
one less than the number of levels for that factor.In this
experiment we decided to analyze surface finish for four different
concentrations ofchemicals. For Acetone concentration levels of
90%, 85%, 80%, 70% were taken and time ofbath of 5 min and 10 min
were found to be suitable on the other hand for Methyl ethyl
ketoneconcentration of 20%, 25%, 30%, 35% were taken, also 3 min
and 6 min were found to besuitable exposure time. These chemicals
have higher diffusion rate at elevated temperaturesso two different
temperatures i.e. 25C and 55C were chosen. 533
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Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEME Table 1 Factors and their
levels for experiment Levels Sr. No. Control Factors 1 2 3 4 1 C (%
of concentration) Chemical 1 70 80 85 90 Chemical 2 20 25 30 35 2
Tp (C) 25-30 50-70 - - 3 Ri (Initial Roughness, m) 0.254 0.3302 - -
4 Tm(Time of exposure in Min.) Chemical 1 5 10 - - Chemical 2 3 6
Initial roughness of the parts was taken as roughness corresponding
to 0.2540 layer thickness and0.3302 layer thickness. Time of
exposure was also identified as factor affecting the results of
chemicaltreatment process. Therefore degrees of freedom (DOF) of
factors are (C(3), Tm(1), Ri(1), Tm(1).Degrees of freedom of their
interactions are (C&Tp (3), C&Tm(3), Tm&Tp(1).
Considering all thefactors and their interactions there are 13
degrees of freedom. Hence this experiment is carried outusing L16,
orthogonal array for 4 factors one at 4 level and 3 at 2 levels to
design the experiments forfinding out the surface roughness of
given parts under the simultaneous variation of 4
differentparameters at different levels as shown in Table
1.Figure1(a) Test Specimen with 0.2540 mm Figure1(b) Test specimen
with 0.3302mm layer thickness layer thickness of Sample1/A1 Figure
1(c) Sample 2/A2 Figure 1(d) Sample 3 Figure 1(e) Sample 4 In
total, L16 has 15 degrees of freedom. The remaining (15-13) two
degrees of freedom are used forerror. The design of experiments
based on the L16 array for the present case is shown in Table
2.Inability to distinguish effect of factors and interactions is
called confounding [16]. As it is expectedthat factors C, Tm, Tp to
interact, no factors are assigned to columns 5, 6 and 7. This is
done to avoidconfounding. The results of surface roughness value of
various FDM samples with combinations ofparameters for chemical 1
are shown in Table 2. Similar results for chemical 2 is shown in
Table 3 534
6. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEME Trials were carried out
according to the various combinations of parameters displayedin the
Orthogonal Array and the results for surfaces roughness values were
recorded. Threereadings were taken on sample1, A11 correspondence
to the top surface, A12 correspondenceto the reading along the
build direction, A13 correspondence to the reading perpendicular
tothe build direction. These were then analyzed to obtain the
optimum condition usingMINITAB software. The Data Means plot for
main effects and interaction plots for Chemical1 is shown in
Fig.2.The S-N ratio plot for main effects and interaction plots for
Chemical 1 isshown in Fig 3. The experimental data was solved using
both Data Means and S-N Ratio. Thecondition was S-N Ratio taken was
Smaller is Better hence we will be accepting the highervalue as
preferred value from the graph where as in means graph lower value
will be taken aspreferred value. Results from both Data Means and
S-N Ratio give the same optimizedcondition. Data Means plot for
main effects and interaction plots for Chemical 2 is shown inFig.4
and S-N ratio plot for main effects and interactions is shown in
Fig.5. Main Effects Plot (data means) for Means Interaction Plot
(data means) for Means concent rat ion temp 25 55 3 concentration
2.5 70 2.0 2 80 concentr ation 85 1.5 90 1 1.0 Mean of Means 0.5 3
temp 25 70 80 85 90 25 55 2 55 roughness t ime temp 1 2.5 2.0 3
time 5 1.5 2 10 1.0 time 1 0.5 0.2540 0.3302 5 10 70 80 85 90 5
10Figure-2 (a) Figure-2 (b) Figure 2-Main effects and Interaction
Plots for data means Main Effects Plot (data means) for SN ratios
Interaction Plot (data means) for SN ratios 25 55 concent ration
temp 10 10 concentration 70 5 80 0 concentr ation 85 0 90 Mean of
SN ratios -5 -10 10 temp -10 25 70 80 85 90 25 55 55 0 temp
roughness time 10 -10 5 10 time 5 0 10 0 time -5 -10 -10 0.2540
0.3302 5 10 70 80 85 90 5 10Signal-to-noise: Smaller is better
Signal-to-noise: Smaller is betterFigure-3 (a) Figure-3 (b) Figure
3-Main effects and Interaction Plots for S-N Ratio 536
7. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEME Table 3 Orthogonal Array
L16 with results of trials for chemical 2 C(1) Tp(2) Ri(3) Tm(4)
CxTp(5) CxTm(6) TpxTm(7) M11 M12 M13 1 1 1 1 2.048 0.594 8.081 1 1
2 2 0.106 0.215 0.082 1 2 1 2 0.147 0.14 0.123 1 2 2 1 2.277 0.526
6.045 2 1 2 1 1.606 1.972 4.247 2 1 1 2 1.312 0.42 3.283 2 2 2 2
1.367 0.291 3.775 2 2 1 1 1.129 0.217 0.33 3 1 2 1 0.097 0.143
0.178 3 1 1 2 0.308 0.253 0.258 3 2 2 2 0.236 0.387 0.32 3 2 1 1
0.16 0.244 0.216 4 1 1 1 0.612 1.279 1.66 4 1 2 2 0.136 1.832 1.294
4 2 1 2 0.137 0.268 0.241 4 2 2 1 2.048 0.594 8.081 Main Effects
Plot (data means) for Means Interaction Plot (data means) for Means
25 55 concentration temp 2.5 4 concentration 20 2.0 25 2 30 1.5
concentr ation 35 1.0 Mean of Means 0 4 0.5 temp 25 20 25 30 35 25
55 55 2 temp roughness time 2.5 2.0 4 0 time 1.5 3 6 1.0 2 time 0.5
0 0.2540 0.3302 3 6 20 25 30 35 3 6Figure-4 (a) Figure-4 (b) Figure
4-Main effects and Interaction Plots for Means (MEK) Main Effects
Plot (data means) for SN ratios Interaction Plot (data means) for
SN ratios concent ration temp 25 55 10 concentration 10 20 5 25 0
concentr ation 30 0 35 Mean of SN ratios -10 -5 temp -10 10 25 20
25 30 35 25 55 55 roughness time temp 0 10 -10 5 time 10 3 0 6 0
time -5 -10 -10 0.2540 0.3302 3 6 20 25 30 35 3 6Signal-to-noise:
Smaller is better Signal-to-noise: Smaller is betterFigure-5 (a)
Figure-5 (b) Figure 5-Main effects and Interaction Plots for S-N
Ratio (MEK) 537
8. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEME3.2 Analysis of variance
The results obtained for surface roughness data from the white
light interferometer (WLI)data are analyzed by using the
statistical tool ANOVA. It determines the relative effect of
theindividual factors and their interactions on the surface
roughness of parts. The analysis byusing ANOVA technique is done
analytically. An equation for total variation may be writtenasSS =
SS C + SS + SS + SS + SS + SS + SS (1) T Tp Ri Tm TmxC TpxC
TmxTpwhere SST is total sum of squares, SSC, SSTp, SSRi, SSTm, are
sum of squares for ConcentrationC, Temperature Tp, Initial
roughness Ri, Time Tm. SSTmxc, SSTpxc, , SSTmXTp are sum ofsquares
of Concentration-Temperature, Concentration -Time and
Time-Temperatureinteractions respectively and SSE is sum of square
of the error. If T is the sum of all (N)Surface roughness values,
the total sum of squares is given by N T 2 (2) SS T = Fi 2 N i = 1
Sum of squares of Concentration(C) factor is given as N Ci 2 T 2SS
C = (3) i=1 N Ci Nwhere, N is the number of levels of Concentration
factor, Ci and NCi are the sum and numberof observations
respectively under ith level. Similarly, sum of squares of other
five factors canalso be calculated. Sum of squares of interaction
of C and Tm is given by n ( CXTm ) T 2 2 = iSS SS SS (4) N C Tm i
=1 CXTm N ( CXTm )iwhere (C xTm)i and N(CXTm)i are the sum and
number of observations (surface roughness)respectively under ith
condition of the combinations of factors C and Tm and n is the
numberof possible combinations of the interacting factors C and Tm.
Similarly, the sum of squaresfor other two interactions can also be
found out. The results obtained from ANOVA forchemical 1 and
chemical 2 are given in Table 4 and Table 5 respectively. 538
9. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEME Table-4 ANOVA table for
Chemical 1 Source DF Seq SS Percent contribution Concentration 3
955.65 65.90 Temp 1 42.45 2.93 Initial roughness 1 105.92 7.30 Time
1 18.84 1.30 Concentration*Temp 3 161.79 11.16 Concentration*Time 3
68.9 4.75 Temp*Time 1 81.09 5.59 Residual Error 2 15.55 1.07 Total
15 1450.2 100.00 Table-5 ANOVA table for Chemical 2 Source DF Seq
SS Percent contribution Concentration 3 770.72 37.78 Temp 1 288.32
14.13 Initial roughness 1 12.13 0.59 Time 1 11.69 0.57
Concentration*Temp 3 644.31 31.59 Concentration*Time 3 286.54 14.05
Temp*Time 1 10.95 0.54 Residual Error 2 15.23 0.75 Total 15 2039.9
100.00 539
10. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEME SepIV. RESULTS All the
test sample from group 1 to 16 having average minimum and
maximumroughness 5.56 micron and 6.67 micron respectively had
experienced reduced roughnessvalue after the chemical treatment.
The minimum average roughness observed is equal to treatment0.175
micron and maximum average roughness equal to 3.47 micron for
Chemical 1 andaverage minimum 0.134 micron and maximum 3.58 micron
for chemical 2. Fig.6 shows maximumeffect of chemical treatment on
average roughness value for chemical 1 and chemical 2. The
roughness values are analyzed on the basis on DOE and ANOVA for
both thechemicals. Following are the detailed explanation of
results:-4.1 CHEMICAL 1 From the ANOVA table (Table 4) we find that
for chemical 1 the most importantfactor is concentration
contributing 65.9%, concentration-temperature interaction is the
concentration temperaturesecond most important factor contributing
11.16% followed by initial roughness 7.3% time ofexposure is the
least significant factor. Fig.2 and Fig.3 also display the similar
results. 7 6 5 4 3 2 1 0 15 16 12 13 14 7 8 9 10 11 Ra(initial) 5 6
Ra(acetone) 4 Ra(MEK) 1 2 3 Ra(initial) Ra(acetone) Ra(MEK) Figure
6 Effect of chemical treatment on average roughness value of Group1
Group1-16It is observed from Fig.2(a) and Fig.3(a) that the optimum
condition is C4-Tp2- Ri1-Tm1 i.e. (a) Flevel 4 for concentration
(90%) , level 2 for temperature (55C) , level 1 for initial
roughness (55C)(corresponding to layer thickness 0.2540 mm) and
level 1 for exposure time (5 min. is the min.)optimum condition
without taking interaction into account. Since it is clear from the
results tion clearfrom ANOVA that concentration temperature
interaction is the second most important factor
concentration-temperaturecontributing 11.16% so when considering
interactions CxTp and Tp xTm we can conclude Tmfrom Fig.2(b) and
Fig.3(b) that the optimum condition is C3-Tp2- Ri1-Tm1. 540
11. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEME4.2 CHEMICAL 2 From Table 5
we find that for chemical 2, concentration, concentration-
temperatureinteraction, temperature and concentration-time
interaction are the most significant factorcontributing 37.78%,
31.59%, 14.13% and 14.05% respectively.From Fig4.(a) and Fig.5(a)
we find that the optimum condition for chemical 2 is C3-Tp2-Ri1-Tm1
i.e. 30% concentration, 55 C temperature of bath, initial roughness
correspondingto 0.2540 mm layer thickness and 3 minutes exposure
time. It is obvious from ANOVAanalysis that concentration -
temperature interaction is the most dominant factor
afterconcentration factor in this chemical treatment process
contributing 31.59% followed byconcentration-time interaction.
Considering both C xTm and CxTp interactions we find fromFig.4 (b)
and Fig.5 (b) that the optimum condition is C3-Tp2-Ri1-Tm2. Samples
were treated at both the conditions without interaction and with
interactionfor both the chemicals 1 & chemical 2. Table 6 shows
the tabulated results and roughnessvalues at optimum levels. It is
clear from Table 6 that optimum condition with interactiongives
better results for both chemical 1 and chemical 2. Condition 1
refers to the optimumcondition without taking account for
interaction while condition 2 refers to optimumcondition when
taking account for interactions. Table 6 Results for optimum
condition and roughness values at optimum levels.Factors Acetone
Methyl Ethyl Ketone Condition 1( Condition Condition 1 Condition 2
C4-Tp2- Ri1- 2(C3-Tp2- Ri1- (C3-Tp2-Ri1- (C3-Tp2-Ri1- Tm1) Tm1)
Tm1) Tm2)C(% of 90 85 30 30concentration)Tp(C) 55 25 55 55Ri
(Initial 0.254 0.254 0.254 0.254Roughness, m)Tm (Time of 5 10 3
6exposure inMin.)Average 0.367 0.175 0.314 0.143roughness value,Ra
( m)Further a comparison is made between results obtained with
chemical 1 and chemical 2 onfour different samples which were
manufactured on Stratasyss Dimension SST 1200 FDMmachine. Sample 1
is a cube as shown in Fig.1(a) & Fig.1(b), sample 2 is shown in
Fig.1(c),sample 3 is shown in Fig.1(d) and sample 4 is shown in
Fig.1(e).The results withcomparisons for chemical 1 and chemical 2
is shown in Table 7. Fig.7 shows the originalpart where as Fig.8
and Fig.9 show the parts treated with Chemical 1 and Chemical
2respectively at their optimum conditions. 541
12. International Journal of Mechanical Engineering and
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Volume 3, Issue 3, Sep- Dec (2012) IAEME Table 7 Comparison between
Chemical 1 and Chemical 2 Chemical 1( Acetone) Chemical 2 (
Methylethylketone)Samples Roughn Aestheti Curi % Roughn Aestheti
Curi % ess at c ng change ess at c ng change optimu appeara Time in
optimu appeara Time in m cond. nce hrs dimensi m cond. nce hrs
dimensi m ons m onsSampl 0.175 Very 1 Less 0.143 Glossy 2 Lesse1
smooth than than 1% 0.5%Sampl 1.13 Very 1 Less 0.98 Glossy 2 Lesse2
smooth than than 1% 0.5%Sampl 0.847 Very 1 Less 0.495 Glossy 2
Lesse3 smooth than than 1% 0.5%Sampl 3.3 Very 1.5 Less 2.12 Glossy
3 Lesse4 smooth than than 1% 0.5% Figure 7(original) Figure
8(Chemical1) Figure 9(Chemical2)The original part as shown in Fig.7
is made of ABS material in white & blue color, but
thechemically treated parts as shown in Fig.8 and Fig.9 are made of
ABS material in whitecolor.The size of the specimen was measured
before and after the chemical treatment process inorder to account
for the variation in dimensions due to chemical treatment process.
Baselengths were taken as l1 and l2 , height of the specimen was
taken as H. Readings were takenby ACCURATE SPECTRA co-ordinate
measuring machine. The results show less than 1%deviation. Detailed
results are shown in Table 8. 542
13. International Journal of Mechanical Engineering and
Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
Volume 3, Issue 3, Sep- Dec (2012) IAEME Table 8 Average change in
dimension after chemical treatment process. Length L1 Length L2
Height H (mm) (mm) (mm)Chemical 1 Average -0.42 -0.51 -0.43
Variance 0.01 0.01 0.01Chemical 2 Average -0.64 -0.68 -0.51
Variance 0.01 0.01 0.01The cost of the chemical treatment process
is compared with the commercially availablesystems and the same is
listed in the Table 9. It is observed from the Table 9 that
theproposed system is economical to use and has very small setup
cost as compared to thecommercial system available in the market.
Table 9 Cost comparison of proposed chemical treatment process with
other available commercial system.Sr. Capital Cost, Depreciation,
Raw Power LabourNo INR(Approx.) INR Material Consumption Cost cost
per cost per per part*, hour, INR hour, INR INR 1. Acetone 10000
2.78 per day 32 6 50 process 2. MEK 10000 2.78 per day 21 6 50
process 3. Commercial 35, 00000 959 per day 42 15 50 system* for
part size 50x50x25 mmV.CONCLUSION In this paper the surface
roughness of FDM prototype parts is addressed, the parameters
thathave significant effect on the surface roughness (Ra) value in
the chemical treatment process havebeen identified. The chemical
treatment process is optimized in terms of solution concentration,
timeof exposure, initial roughness and temperature of the chemical
bath using Design of Experiments andANOVA. Two different chemical
were taken, i.e. Dimethyl ketone (Acetone) and Methyl ethyl
ketone(MEK), in case of Acetone it was observed that the solution
concentration, concentration-temperatureinteraction and the initial
roughness are the most significant factors. For Methyl ethyl ketone
chemicaltreatment process, it was observed that the concentration,
concentration - temperature interaction andconcentration-time
interaction are the most important factors, surprisingly for MEK
the initialroughness and time of exposure have negligible effect on
the process. The process was applied forsimple parts to complex
free form parts. The optimum levels for the parameters for
chemicaltreatment process are found out which shows drastic
improvement in surface finish. The appearanceof the finished parts
is comparable to plastic moulded parts, the parts have glossy
finish and themaximum curing time is about 2 to 4 hours. The
process is very much economical compared to othercommercial systems
available in the market. Further studies can be carried out to
commercialize thisprocess to make it available in the market at an
affordable price. 543
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Technology (IJMET), ISSN 0976 6340(Print), ISSN 0976 6359(Online)
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