Home Optimization of Injection Molding Process for SGF and PTFE Reinforced PC Composites Using Response Surface Methodology and Simulated Annealing Approach
Article
Licensed
Unlicensed Requires Authentication

Optimization of Injection Molding Process for SGF and PTFE Reinforced PC Composites Using Response Surface Methodology and Simulated Annealing Approach

  • T. Yang , Y.-K. Yang and C.-Y. Chen
Published/Copyright: April 6, 2013
Become an author with De Gruyter Brill

Abstract

This study is analyzed variations of ultimate strength, friction coefficient and wear mass loss that depend on the injection molding techniques during the blending of short glass fiber (SGF) and polytetrafluoroethylene (PTFE) reinforced polycarbonate (PC) composites. A hybrid method including response surface methodology (RSM) and back-propagation neural network (BPNN) integrating simulated annealing algorithm (SAA) are proposed to determine an optimal parameter setting of the injection molding process. The specimens are prepared under different injection molding processing conditions based on a Taguchi orthogonal array table. The results of eighteen experimental runs were utilized to train the BPNN predicting ultimate strength, friction coefficient and wear mass loss. Simultaneously, the RSM and SAA approaches were individually applied to search for an optimal setting. In addition, the analysis of variance (ANOVA) was implemented to identify significant factors for the injection molding process parameters and the result of BPNN integrating SAA was also compared with RSM approach. The results of optimal parameters of injection molding process for the ultimate strength of x-direction and y-direction based on BPNN/SAA approach were increased 3.12%, and 6.18%, respectively.


Mail address: Yung-Kuang Yang, Department of Mechanical Engineering, Minghsin University of Science and Technology, 1, Hsin Hsing Road, Hsin Feng, 304 Hsinchu, Taiwan, ROC. E-mail:

References

Alsewailem, F. D., Gupta, R. K., “Mechanical Properties of Rubber-Toughened Post-industrial Glass-fiber-reinforced PA 66”, Int. Polym. Proc., 21, 189197(2006)Search in Google Scholar

Altan, M., Yurci, M. E., “Optimization of Residual Stresses in the Surface Regions of Injection Moldings”, Polym. Plast. Tech. Eng., 49, 3237(2010), DOI: http://dx.doi.org/10.1080/03602550903206399Search in Google Scholar

Arul, S., et al., “Modeling and Optimization of Process Parameters for Defect Toleranced Drilling of GFRP Composites”, Mater. Manuf. Process., 21, 357365(2006), DOI: http://dx.doi.org/10.1080/10426910500411587Search in Google Scholar

Brent, S. A.: “Plastics Materials and Processing”, 3rd Edition, Prentice Hall, New Jersey, (2006)Search in Google Scholar

Biswas, S., Satapathy, A., “Erosion Wear Analysis of SiC Filled Glass-Epoxy Composites using Taguchi Technique”, Int. Polymer. Proc., 25, 2333(2010), DOI: http://dx.doi.org/10.3139/217.2284Search in Google Scholar

Carriœn, F. J., et al., “Influence of ZnO Nanoparticle Filler on the Properties and Wear Resistance of Polycarbonate”, Wear, 262, 15041510(2007), DOI: http://dx.doi.org/10.1016/j.wear.2007.01.016Search in Google Scholar

Carriœn, F. J., et al., “Physical and Tribological Properties of a New Polycarbonate-organoclay Nanocomposite”, Eur. Polym. J., 44, 968977(2008), DOI: http://dx.doi.org/10.1016/j.eurpolymj.2008.01.038Search in Google Scholar

Cheng, W. S., et al., “Investigation of the Effects of Injection Molding Processing Parameters on Conductive Polymeric Composites for Electromagnetic Interference Shielding Effectiveness”, Polym. Plast. Tech. Eng., 48, 216220(2009), DOI: http://dx.doi.org/10.1080/03602550802634592Search in Google Scholar

Chen, C. P., et al., “Simulation and Experimental Study in Determining Injection Molding Process Parameters for Thin-shell Plastic Parts via Design of Experiments Analysis”, Expert. Syst. Appl., 36, 1075210759(2009), DOI: http://dx.doi.org/10.1016/j.eswa.2009.02.017Search in Google Scholar

Chuang, M. T., et al., “Modeling and Optimization of Injection Molding Process Parameters for Thin-shell Plastic Parts”, Polym. Plast. Tech. Eng., 48, 745753(2009), DOI: http://dx.doi.org/10.1080/03602550902824630Search in Google Scholar

Chen, H. C., et al., “Optimization of Wire Electrical Discharge Machining for Pure Tungsten using a Neural Network Integrated Simulated Annealing Approach”, Expert. Syst. Appl., 37, 71477153(2010), DOI: http://dx.doi.org/10.1016/j.eswa.2010.04.020Search in Google Scholar

Davim, J. P., et al., “An Investigative Study of Delamination in Drilling of Medium Density Fibre Board (MDF) using Response Surface Models”, Int. J. Adv. Manuf. Tech., 37, 4957(2008), DOI: http://dx.doi.org/10.1007/s00170-007-0937-8Search in Google Scholar

Gu, A., et al., “Novel Preparation of Glass Fiber Reinforced Polytetrafluoroethylene Composites for Application as Structural Materials”, Polymer. Adv. Tech., 20, 3942(2009), DOI: http://dx.doi.org/10.1002/pat.1243Search in Google Scholar

Kurt, M., et al., “Application of Taguchi Methods in the Optimization of Cutting Parameters for Surface Finish and Hole Diameter Accuracy in Dry Drilling Processes”, Int. J. Adv. Manuf. Tech., 40, 458469(2009), DOI: http://dx.doi.org/10.1007/s00170-007-1368-2Search in Google Scholar

Karunakar, D. B., Datta, G. L., “Prevention of Defects in Castings using Back Propagation Neural Networks”, Int. J. Adv. Manuf. Tech., 39, 11111124(2008), DOI: http://dx.doi.org/10.1007/s00170-007-1289-0Search in Google Scholar

Lin, S. S., et al., “Optimization of Mechanical Characteristics of Short Glass Fiber and Polytetrafluoroethylene Reinforced Polycarbonate Composites via D-optimal Mixture Design”, Polymer. Plast. Tech. Eng., 49, 195203(2010), DOI: http://dx.doi.org/10.1080/03602550903284297Search in Google Scholar

Lin, Y. C., et al., “Machining Performance and Optimizing Machining Parameters of Al2O3-TiC Ceramics Using EDM Based on the Taguchi Method”, Mater. Manuf. Proc., 24, 667674(2009), DOI: http://dx.doi.org/10.1080/10426910902769285Search in Google Scholar

Lotti, C., Bretas, R. E. S., “Correlation between Injection Molding Parameters, Morphology and Mechanical Properties of PPS/SEBS Blend Using Artificial Neural Networks”, Int. Polym. Proc., 22, 105116(2007)Search in Google Scholar

Mergler, Y. J., et al., “Influence of Yield Strength and Toughness on Friction and Wear of Polycarbonate”, Wear, 258, 915923(2005), DOI: http://dx.doi.org/10.1016/j.wear.2004.09.046Search in Google Scholar

Montgomery, D. C.: “Design and Analysis of Experiment”, 6th Edit., John Wiley and Sons, New York(2005)Search in Google Scholar

Phua, Y. J., et al., “Injection Molded Short Glass and Carbon Fibers Reinforced Polycarbonate Hybrid Composites: Effects of Fiber Loading”, J. Reinfor. Plast. Compos., 29, 25922603(2010), DOI: http://dx.doi.org/10.1177/0731684409358282Search in Google Scholar

Patel, K. M., et al., “Determination of an Optimum Parametric Combination Using a Surface Roughness Prediction Model for EDM of Al2O3/SiCw/TiC Ceramic Composite”, Mater. Manuf. Process., 24, 675682(2009), DOI: http://dx.doi.org/10.1080/10426910902769319Search in Google Scholar

Qiao, H., “A Systematic Computer-aided Approach to Cooling System Optimal Design in Plastic Injection Molding”, Int. J. Mech. Sci., 48, 430439(2006), DOI: http://dx.doi.org/10.1016/j.ijmecsci.2005.11.001Search in Google Scholar

Rizvi, S. J. A., Bhatnagar, N., “Optimization of Microcellular Injection Molding Parameters”, Int. Polym. Proc., 24, 399405(2009), DOI: http://dx.doi.org/10.3139/217.2263Search in Google Scholar

SadAbadi, H., Ghasemi, M., “Study on Fiber Weight Fraction Effect on Tensile Modulus of Polystyrene (PS) Composites Reinforced with Short Glass Fiber (SGF) Based on Their Fiber Orientation”, Polymer. Plast. Tech. Eng., 47, 427432(2008), DOI: http://dx.doi.org/10.1080/03602550801898354Search in Google Scholar

Sayarshad, H. R., Ghoseiri, K., “A Simulated Annealing Approach for the Multi-periodic Rail-car Fleet Sizing Problem”, Comput. Oper. Res., 36, 17891799(2009), DOI: http://dx.doi.org/10.1016/j.cor.2008.05.004Search in Google Scholar

Sawyer, W. G., et al., “A Study on the Friction and Wear Behavior of PTFE Filled with Alumina Nanoparticles”. Wear., 254, 573580(2003)10.1016/S0043-1648(03)00252-7Search in Google Scholar

Tzeng, C. J., Yang, Y. K., “Determination of Optimal Parameters for SKD11 CNC Turning Process”, Mater. Manuf. Process., 23, 363368(2008), DOI: http://dx.doi.org/10.1080/10426910801937975Search in Google Scholar

Xiang, D., et al., “On the Tribological Properties of PTFE Filled with Alumina Nanoparticles and Graphite”, J. Reinforc. Plast. Compos., 26, 331339(2007), DOI: http://dx.doi.org/10.1177/0731684407072517Search in Google Scholar

Yang, Y. K., et al., “A Study of Taguchi and Design of Experiments Method in Injection Molding Process for Polypropylene Components”, J. Reinfor. Plast. Compos., 27, 819834(2008), DOI: http://dx.doi.org/10.1177/0731684407084988Search in Google Scholar

Yang, S. H., et al., “Optimization of Electric Discharge Machining Using Simulated Annealing”, J. Mater. Process. Tech., 209, 44714475(2009), DOI: http://dx.doi.org/10.1016/j.jmatprotec.2008.10.053Search in Google Scholar

Zhang, X., et al., “On Dry Sliding Friction and Wear Behavior of PPESK Filled with PTFE and Graphite”, Tribol. Int., 41, 195201(2008), DOI: http://dx.doi.org/10.1016/j.triboint.2007.08.003Search in Google Scholar

Zhang, J., et al., “A New Family of Low Wear, Low Coefficient of Friction Polymer Blend Based on Polytetrafluoroethylene and an Aromatic Thermosetting Polyester”, Polymer. Adv. Tech., 19, 11051112(2008), DOI: http://dx.doi.org/10.1002/pat.1086Search in Google Scholar

Zhang, J. Z., Chen, J. C., “Surface Roughness Optimization in a Drilling Operation Using the Taguchi Design Method”, Mater. Manuf. Process., 24, 459467(2009), DOI: http://dx.doi.org/10.1080/10426910802714399Search in Google Scholar

Zhang, Y., et al., “Optimization for Loading Paths of Tube Hydroforming Using a Hybrid Method”, Mater. Manuf. Process., 24, 700708(2009), DOI: http://dx.doi.org/10.1080/10426910902769392Search in Google Scholar

Received: 2011-01-24
Accepted: 2011-06-04
Published Online: 2013-04-06
Published in Print: 2011-11-01

© 2011, Carl Hanser Verlag, Munich

Articles in the same Issue

  1. Contents
  2. Contents
  3. Regular Contributed Articles
  4. Applicability of the Impact Response Analysis Method for Reinforced Concrete Beams Mixed with Polyvinyl Alcohol Short Fibers
  5. Epoxy-Montmorillonite Nanocomposites Applied to Powder Coatings
  6. Direct Imprinting Using Magnetic Nickel Mold and Electromagnetism Assisted Pressure for Replication of Microstructures
  7. Automated Mold Heating System Using High Frequency Induction with Feedback Temperature Control
  8. The Prediction of Bowing Distortion of Film after Transverse Stretching with Consideration of Heated Air Flow in a Tenter
  9. The Influence of Injection Molding and Injection Compression Molding on Ultra-high Molecular Weight Polyethylene Polymer Microfabrication
  10. A Design-of-Experiment Study on the Microcellular Extrusion of Sub-critical CO2 Saturated PLA Pellets
  11. Optimization of Injection Molding Process for SGF and PTFE Reinforced PC Composites Using Response Surface Methodology and Simulated Annealing Approach
  12. Flow Visualisation in Co-rotating Twin Screw Extruders: Positron Emission Particle Tracking and Numerical Particle Trajectories
  13. The Influence of Melt and Process Parameters on the Quality and Occurrence of Part Defects in Water-assisted Injection Molded Tubes
  14. Model and Numerical Simulation for the Second Penetration in Water-assisted Injection Molding
  15. Influence of Extrusion Conditions on the Rheological Behavior of Nuclear Bituminized Waste Products
  16. Influence of Dicumyl Peroxide Content on Thermal and Mechanical Properties of Polylactide
  17. Rapid Communications
  18. Calculation of Average Residence Time in a Ko-kneader
  19. PPS-News
  20. PPS News
Downloaded on 31.10.2025 from https://www.degruyterbrill.com/document/doi/10.3139/217.2488/pdf
Scroll to top button