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30120130404044

  1. 1. 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) www.jifactor.com IJMET © I A E M E
  2. 2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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:
  3. 3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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.
  4. 4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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
  5. 5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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
  6. 6. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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
  7. 7. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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
  8. 8. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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
  9. 9. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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
  10. 10. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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
  11. 11. 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 International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – August (2013) © IAEME of individual factors %Contribution Rank 1 4 3 5 2
  12. 12. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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.
  13. 13. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print), ISSN 0976 – 6359(Online) Volume 4, Issue 4, July - August (2013) © IAEME 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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