30120130404044

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME
401
IMPROVEMENT OF TOUGHNESS AND STIFFNESS OF BIOPOLYMER
BLENDS USING PCA BASED TAGUCHI APPROACH
R.Umamaheswarrao1
, T.VenkataSylaja2
, Dr. K N S Suman3
1
(Associate professor, Department of Mechanical Engineering, GMRIT, INDIA)
2
(PG Student Department of Mechanical Engineering, GMRIT, INDIA)
3
(Assistant Professor Department of Mechanical Engineering, A U, Visakhapatnam)
ABSTRACT
Biodegradable polymeric blends were widely used in the present days and the focus was
made towards them. To make them more useful for wider applications among the human kind, the
present study has been made to increase their mechanical properties toughness and stiffness. In order
to achieve the improved properties, PCA based Taguchi technique has been selected and its
methodology was implemented .To prepare the blend melt blending technique has been implemented
and to obtain the specimen compression molding process was used by assuming five process
parameters like temperature, pressure, soak time, cooling rate and composition of the blend. In this
PCA method multiple objectives of the optimization problem were converted into a single objective
function known as the principal component. After finding out the principal component the S/N ratios
are plotted and the optimum parameter settings were tabulated.
Keywords: Biodegradable polymeric blends, toughness and stiffness.
I. INTRODUCTION
Plastics play a significant role in the environmental, societal and economic dimensions of
sustainable development. But due to their origin from petroleum based products which were
disintegrating and due to their adverse effects on environment, there was a growing need for an
alternative. Biopolymers were the best alternative since they easily get degraded and they were
originated from plants, which restricts our utilization of petroleum products. Of the many bio-based
and biodegradable polymers, poly-lactic acid (PLA) has been attracting much attention due to its
mechanical properties resembling that of present day commodity plastics such as PE, PP and PS. It
can be processed using injection-molding, compression-molding, extrusion, thermoforming etc. PLA
has high modulus, reasonable strength, excellent flavor and aroma barrier capability, good heat seal
INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING
AND TECHNOLOGY (IJMET)
ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
Volume 4, Issue 4, July - August (2013), pp. 401-413
© IAEME: www.iaeme.com/ijmet.asp
Journal Impact Factor (2013): 5.7731 (Calculated by GISI)
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IJMET
© I A E M E

402
ability and can be readily fabricated, thereby making it one of the most promising biopolymers for
varied applications. Despite these desirable features, several drawbacks tend to limit its widespread
applicability such as high cost, brittleness, and narrow processing windows. Polymer blending was a
method for obtaining properties that the individual do not possess. Biodegradable polymer such as
with poly (butylenessuccinatedadipate) (PBSA) (A Bhatia, R Gupta 2007), poly (butylene adipate-
co-terephthalate) (PBAT) (JT Yeh, CH Tsou, CY Huang, 2010), poly (e caprolactone) (PCL) (Todo
et al., 2007) and poly (ethylene succinate) (PES) (Lu, Qiu, and Yang, 2007), etc are among the better
alternatives for blending with PLA.
Apart from the above mentioned polymers Poly (€ - caprolactone) (PCL) was another
polymer which seems to be promising due to its encouraging properties and its compatibility with
many types of polymers (Hung and Edelman, 1995). To prepare the blends of these polymers Melt
blending setup is used, and molded into a sheet of ASTM standards to carry out the experiment. The
experiments were carried out according to the Taguchi orthogonal array by taking the process
parameters as Temperature, pressure, soak time, cooling rate and composition. After obtaining the
Toughness and Stiffness values PCA method was applied to obtain the Signal to noise ratios,
ANOVA is calculated, optimum values were tabulated.
II. PCA BASED TAGUCHI METHOD
1. Getting experimental data
The experimental values for the four output responses are tabulated and are taken
to optimization.
2. Normalization of experimental data
As the desired optimal setting is for higher Tensile Strength, Elongation, Flexural
Strength and Impact Strength, the experimental data is normalized by using the higher-the-
better (HB) criterion.
Higher-the-better (HB) criterion, the normalized data can be expressed as:
( ) ( ) ( )
( ) ( )kyky
kyky
kx
ii
ii
i
minmax
min
−
−
=
Here xi(k) is the value after the grey relational generation, min yi (k) is the smallest
value of yi (k) for the kth
response, and max yi(k) is the largest value of yi(k) for the kth
response.
3. Calculation of Variance-Covariance matrix
3.1 Calculating the mean of X using the following formula:
Similarly calculate Mean Y, Mean Z, Mean W.
3.2 The formulas used for variance and covariance are:

403
Then calculate x= (xi – Mean X), y= (yi – Mean Y).
Then calculate x2
, y2
, xy.
3.3 Variance-covariance matrix for the four variables will be
Cov(x, x) cov(x, y)
Cov(x, x) cov(x, y)
4. Finding Eigen values and Eigen vectors of the variance-covariance matrix.
5. Calculation of Accountability proportion and Cumulative Accountability proportion.
6. Calculation of individual principal components and composite principal components.
GETTING EXPERIMENTAL DATA
NORMALIZATION OF EXPERIMETAL
CALCULATION OF VARIANCE COVARIANCE
FIND THE EIGEN VALUE ANFD EIGEN
VECTORS OF VARIANCE AND COVARIANCE
MATRIX
CALCULATING ACCOUNTABILITY
PROPORTION AP &CAP
CALCULATION OF INDIVIDUAL PRINCIPAL
COMPONENTS (Ψi)
CALCULATION OF COMPOSITE PRINCIPAL
COMPONENT
CALCULATION OF S/N RATIO
ANOVA
PLOT FOR OPTIMAL PARAMETER SETTING
FOR CPC(Ψi)
Figure – 2.1: Schematic representation of PCA based approach.

404
III. EXPERIMENTATION
A. Materials used
1) POLYLACTIC ACID(PLA)
Table 3.1 Properties of PLA
Fig 3.1 Poly Lactic Acid
2) POLYCAPROLACTANE(PCL)
Table3.2 Properties of PCL
Fig3.2 PolyCaproLactane (PCL)
3) Blend preparation
The pellets of both PLA and PCL were initially dried in vacuum oven at a temperature of
50o
C for 2 days to remove water before processing through the Rheomix shown in Fig.3.3. Drying is
necessary to minimize the hydrolytic degradation of the polymers during melt processing in the
HakeeRheomix. Blends of PLA and PCL with 90/10, 80/20, 70/30 were extruded by melt blending at
170o
C (zone-5).Measured quantities of each polymer were first mixed in a container before blending
in aHakeeRheomix.The Rheomix was operated at 170o
C,160o
C,150o
C, 140o
C and130o
C at zones 5,
4, 3, 2 and 1 respectively and 60 rpm screw speed for compounding of all the blends. After
compounding the blend was extruded through an orifice of 1mm diameter and pelletized using a
pelletize as shown in Fig.3.4. All the blends were given the same processing treatment to maintain
the overall consistency. Prepared blends were again dried at 50o
C in vacuum oven for 12 hours
before compression.
Tensile modulus 2.7-16 Gpa
Melting index 8/10 g/min
Density 1.21-1.43 g/cm3
Crystalinity 37% _
Melting index 7/10 g/min
Density 1.02-1.12 g/cm3
Melting point 60 o
C

405
B) Experimental design
1) In order to determine optimum process parameters and effect of process control parameters
Taguchi orthogonal array was selected. The controllable parameters are taken as Pressure (P),
Temperature (T), Soak time(S), Cooling rate (CR), Composition(C). Five controllable parameters
with four levels were studied as shown in Table – 3.3
Table 3.3: Process control parameters
2) Taguchi L16 OA design was used for Experimentation. As mentioned in table 3.4.
Table 3.4: Taguchi L16 OA design
Process
Parameters
Notation Units Level 1 Level 2 Level 3 Level 4
Temperature T 0
C 170 175 180 185
Pressure Pr M Pa 2.5 5 7.5 10
Soak Time ST Min 0 10 20 30
Cooling System CS --- Natural Forced Water --
S.NO T P S T CS C
1 170 2.5 5 N 0
2 170 5 10 F 10
3 170 7.5 15 W 20
4 170 10 20 F 30
5 175 2.5 10 W 30
6 175 5 5 F 20
7 175 7.5 20 N 10
8 175 10 15 F 0
9 180 2.5 15 F 10
10 180 5 20 W 0
11 180 7.5 5 F 30
12 180 10 10 N 20
13 185 2.5 20 F 20
14 185 5 15 N 30
15 185 7.5 10 F 0
16 185 10 5 W 10

406
3) Specimen preparation as per DOE
Specimen of 25mmx6mmx4mm are prepared by compression molding at 180o
C and 13MPa
Fig3.3 Hot Press
MODEL: MPE-15-300 TONS. Air cooling
Fig 3.4 Compression molding plates
Fig 3.5: Compression molded specimen

407
Pellets of PLA/PCL blends were kept in a flash picture frame mould( as shown fig 3.4) and placed
between the hot plates of hydraulic press(as shown fig 3.3). The assembly is heated and compressed
for the measured amount of time. Then, the polymer is cooled to room temperature at a specified
cooling rate under constant pressure. Then the hot pressed sheet is removed from the flash picture
frame mould and conditioned at 25o
C of for 24 hours .The specimens were cut as per ASTM
standered using wire hacksaw.the specimen as shown in fig 3.5.
4) Toughness and Stiffness measurement.
The compression molded specimen is carried out to characterization in an INSTRON -3382
model UTM which is equipped with 100KN load cell, gauge length of 50mm and crosshead speed of
5 mm/min. Tensile testing was carried out according to the ASTM D 638-08 (Type- I), a standard
test method for determining tensile properties of plastics. The area under Stress-Strain curve
evaluates to Toughness and slope to Stiffness.and the resultant values of all tests were tabulated in
table 3.5.
Fig3.6: Universal testing machine

408
Table 3.5: Taguchi L16 OA design Experimental results
S.NO
T P S T CS C
Experimental results
Toughness(J/m2
) Stiffness(N/m2
)
1 170 2.5 5 N 0 98.46 2.32
2 170 5 10 F 10 121.16 1.83
3 170 7.5 15 W 20 235.34 1.87
4 170 10 20 F 30 72.21 0.67
5 175 2.5 10 W 30 253.85 1.85
6 175 5 5 F 20 229.4 2.3
7 175 7.5 20 N 10 184.95 2.6
8 175 10 15 F 0 150.5 2.9
9 180 2.5 15 F 10 169.97 2.51
10 180 5 20 W 0 169.05 2.31
11 180 7.5 5 F 30 194.58 1.67
12 180 10 10 N 20 194.9 2.38
13 185 2.5 20 F 20 176.22 1.97
14 185 5 15 N 30 87.65 1.73
15 185 7.5 10 F 0 129.51 2.28
16 185 10 5 W 10 189.55 2.87

409
IV. RESULTS AND DISCUSSIONS
Results obtained through Experimentation (table3.4) were normalized and the resulting
values are tabulated in table 4.1.
Table 4.1 normalized data
S.NO T P S T CS C
NORMALIZED DATA
Toughness(J/m2
) Stiffness(N/m2
)
1 1 1 1 1 1 0.1445 0.7399
2 1 2 2 2 2 0.2694 0.5201
3 1 3 3 3 3 0.8980 0.5381
4 1 4 4 2 4 0 0
5 2 1 2 3 4 1 0.5291
6 2 2 1 2 3 0.8653 0.7309
7 2 3 4 1 2 0.6206 0.8654
8 2 4 3 2 1 0.4310 1
9 3 1 3 2 2 0.5382 0.8251
10 3 2 4 3 1 0.5331 0.7354
11 3 3 1 2 4 0.6376 0.4484
12 3 4 2 1 3 0.6754 0.7668
13 4 1 4 2 3 0.5726 0.5515
14 4 2 3 1 4 0.0850 0.4753
15 4 3 2 2 1 0.3154 0.7219
16 4 4 1 3 2 0.6460 0.9865

410
Normalized data (table4.1) converted into principal components. and the resulting values are
tabulated in table4.2.
Table 4.2: Principal components
Composite principal components are calculated using principal components (table4.2) are shown in
table 4.3. Further: S/N ratios are concluded from composite principal components. obtained results
are also presented in table 4.3.
Table 4.3: S/N ratios for composite principal components
Trail no
Composite principal
component
S/N ratio
1 1.0661 0.5563
2 0.8283 -1.6357
3 0.4562 3.4082
4 0 0
5 1.5999 4.0822
6 1.6018 4.0924
7 1.5060 3.5566
8 1.5399 3.7502
9 1.3931 2.8800
10 1.2837 2.1695
11 1.1443 1.1713
12 1.4450 3.1979
13 1.1407 1.1438
14 0.6828 -3.3136
15 1.1141 0.9385
16 1.6676 4.4420
Trail no ψ 1 (1st
P.C) ψ 2 (2nd
P.C)
1 -0.5954 0.8844
2 -0.2507 0.7895
3 0.3599 1.4361
4 0 0
5 0.4709 1.5291
6 0.1344 1.5962
7 -0.2448 1.4860
8 -0.5690 1.4310
9 -0.2869 1.3633
10 -0.1972 1.2685
11 -0.2252 1.1220
12 -0.0914 1.4422
13 -0.1942 1.1241
14 -0.3903 0.5603
15 -0.4065 1.0373
16 -0.3045 1.6325

International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976
6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July
The stastical analysis tool ANOVA was used to analyze the contribution
on output responses. And respective contributions are presented in table
Table 4.4: ANOVA analysis
Figure 4.1: S/N plots f
Source of
variation(SV)
DOF
Sum
squares
Temperature 3 2.054357
Pressure 3 0.136679
Soak time 3 0.41253
Cooling type 2 0.0676
Composition 3 0.54291
Residual 1 0.03703
Total 15
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976
6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME
411
ANOVA was used to analyze the contribution of individual factors
on output responses. And respective contributions are presented in table 4.4.
ANOVA analysis for composite quality indicator
S/N plots for principal component analysis
Sum of
squares
Mean sum
of squares
F-ratio %Contribution
2.054357 0.6847 18.488 63.25
0.136679 0.0455 1.230 4.20
0.41253 0.1375 3.7127 12.70
0.0676 0.0338 0.9131 3.12
0.54291 0.1809 4.8861 16.71
0.03703 0.0370
August (2013) © IAEME
of individual factors
%Contribution Rank
1
4
3
5
2

412
By using S/N ratio, the S/N ratio plots are obtained. As shown in fig4.1.the Optimum levels
of each factor has been concluded and presented in table 4.5.
Table 4.5: Optimum levels for each process parameters
Trail
no
Process parameters Optimum levels Optimum values
1 Temperature 2 1750
C
2 Pressure 4 10M pa
3 Soak Time 1 0
4 Cooling type 3 Quenched
5 Composition 3 20%
VI. CONCLUSION
Application of PCA can eliminate multi co linearity of the output responses and transform
these correlated responses into uncorrelated quality indices called principal components. Absence of
correlation between the responses is the basic assumption for applying Taguchi optimization
technique. It can be recommended that the PCA based hybrid Taguchi method is good, for example,
in the case of process (chemical and pharmaceutical) industries when there are hundreds of response
variables. In our experimentation from the previously presented experimental results and analysis
tables it can be concluded that five parameters influencing output responses with varying percentage.
The optimum levels of each factor are temperature at level 2 and the optimum value is 1750
C.
Pressure at level 4 and the optimum value is 10M pa. Soak Time at level 1 and the optimum value is
0. Cooling type at level 3 and the optimum value is quenched. Composition at level 3 and the
optimum value is 20% are concluded.
VII. ACKNOWLEDGMENT
The satisfaction that accompanies the successful completion of any task would be incomplete
without introducing the people who made it possible and whose constant guidance and
encouragement crowns all efforts with success.
I express my sincere gratitude to and sri R.Umamaheswarrao, Department of Mechanical
Engineering. GMRIT Rajam. , Dr K N S Suman, Assistant professor department of mechanical
engineering, A U, Visakhapatnam
We are highly indebted to him for his guidance, timely suggestions at every stage and
encouragement to complete this project work successfully.
Last but not the least we are deeply indebted to our family for all their support and who stood
behind me to get this project completed in time. We are thankful to All Mighty for providing us with
this opportunity.

413
VIII. REFERENCES
[1] A Bhatia, R Gupta… - Korea-Australia …, 2007”Compatibility of biodegradable poly (lactic
acid)(PLA) and poly (butylene succinate)(PBS) blends for packaging application”.
[2] JT Yeh, CH Tsou, CY Huang, KN Chen… - Journal 2010” Compatible and crystallization
properties of poly (lactic acid)/poly (butylene adipate‐co‐terephthalate) blends”.
[3] Mitsugu Todo1 and Tetsuo Takayama2 2007 “Fracture Mechanisms of Biodegradable
PLAand PLA/PCL Blends”.
[4] Lu, J., Qiu, Z., and Yang, W., 2007”, Fully biodegradable blends of poly (l-lactide) and poly
(ethylene succinate): Miscibility, crystallization, and mechanical properties. Polymer. 48:
4196-4204.
[5] Hung, S.J., & Edelman, P.G. 1995”, An overview of biodegradable polymers and
biodegradation of polymers. In G.Scott and D.Gilead (Eds.), Degradable polymers: principles
and application (pp.8-24). London: Champman and Hall.
[6] Lee, S. and Lee, J. W., 2005, Characterization and processing of Biodegradable polymer
blends of poly (lactid acid) with poly (butylenes succinate adipate). Korea-Australia
Rheology Journal. 17: 71-77.
[7] Jiang, L., Wolcott, M. P., and Zhang, J., 2006, Study of Biodegradable Polylactide/Poly
(butylenesadipate-co-terephthalate) Blends. Biomacromolecules. 7: 199-207.
[8] Todo, M., Park, S. D., Takayama, T., and Arakawa, K., 2007, Fracture micro mechanisms of
bioabsorbable PLLA/PCL polymer blends. EngFract Mech. 74: 1872-1883.
[9] Pravin R. Parate and Dr. Ravindra B. Yarasu, “Optimization of Process Parameters of
Lapping Operation by Taguchi Approach for Surface Roughness of SS 321”, International
Journal of Mechanical Engineering & Technology (IJMET), Volume 4, Issue 4, 2013,
pp. 15 - 21, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359.
[10] S.Shankar, Dr.H.K.Shivanand and Santhosh Kumar.S, “Experimental Evaluation of Flexural
Properties of Polymer Matrix Composites”, International Journal of Mechanical Engineering
& Technology (IJMET), Volume 3, Issue 3, 2012, pp. 504 - 510, ISSN Print: 0976 – 6340,
ISSN Online: 0976 – 6359.

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