Startseite Correlations between Injection Molding Parameters, Morphology and Mechanical Properties of PPS Using Artificial Neural Networks
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Correlations between Injection Molding Parameters, Morphology and Mechanical Properties of PPS Using Artificial Neural Networks

  • C. Lotti und R. E. S. Bretas
Veröffentlicht/Copyright: 6. April 2013
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International Polymer Processing
Aus der Zeitschrift International Polymer Processing Band 21 Heft 2

Abstract

The processing conditions of injection molding have a complex influence on the morphology and on the mechanical properties of a semicrystalline polymer. Therefore, to establish correlations between processing conditions, morphology and mechanical properties constitutes a difficult task; finding these correlations is one of the goals of a materials engineer.

The purpose of this work was to study the influence of the injection molding conditions on the morphology and mechanical properties of poly(p-phenylene sulphide), PPS, using artificial neural networks, ANNs. First, a statistical analysis was done to find the more influential processing parameters that affect the morphology and mechanical properties of the PPS. Second, ANNs were applied to establish correlations between processing conditions, morphology and properties.

It was found that the variables with the highest influence on the morphology and the mechanical properties were the injection and mold temperatures (Tinj and Tmold, respectively), as they showed a straight relationship with the crystallinity index of the injection molded part.

Three different ANNs were built to predict the correlations. The ANN-1 predicted the crystallinity gradient along the thickness of the injection molded part from Tmold, Tinj, and flow rate, Q; the ANN-2 predicted the elastic and flexural modulus, E, and the yield stress from the crystallinity gradient, while the ANN-3 predicted the mechanical properties directly from the processing conditions. All ANNs were built with only fifteen experimental data and were trained with the group cross-validation method, GCV and with a training-test set method. Both methods showed similar and excellent performance. Thus, it can be concluded that ANNs can be used as a powerful tool in the learning of these complex correlations.

∗ Mail address: R. E. S. Bretas, Department of Materials Engineering, Universidade Federal de São Carlos, 13565-905 São Carlos, SP, Brasil. E-mail:

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Received: 2005-4-4
Accepted: 2005-11-4
Published Online: 2013-04-06
Published in Print: 2006-05-01

© 2006, Hanser Publishers, Munich

Artikel in diesem Heft

  1. Contents
  2. Contents
  3. Regular Contributed Articles
  4. Pressure and Temperature Dependence of LDPE Viscosity and Free Volume: The Effect of Molecular Structure
  5. Correlations between Injection Molding Parameters, Morphology and Mechanical Properties of PPS Using Artificial Neural Networks
  6. Investigations into Kinematic Reversal in Non-isothermal Flows in Single-screw Machines
  7. The Effect of Post-extrusion Conditions in Ribbon Extrusion of Polymer Blends
  8. Effect of the Chemical and Morphological Conditions of the Die Wall on the Extrusion of Linear Polyolefins
  9. Investigation of the Heat Affected Zone of Hot-gas Welded PP Joints
  10. Method for the Optimisation of Screw Elements for Tightly Intermeshing, Co-rotating Twin Screw Extruders
  11. Rheology and Processing of Molten Poly(methyl methacrylate) Resins
  12. PLLA Morphology Controlled by Dry-cast Process
  13. Two Component Injection Molding of Phase Separating Blends
  14. A Low Force Valve for Dynamic Control of Molten Plastics in a Mold
  15. Influence of Drawing and Temperature on the Optical and Structural Properties of Monofilament PP Sutures
  16. Mechanical Properties of Rubber-toughened Post-industrial Glass-fiber-reinforced PA66
  17. Thermal Flow Instability in Metal Injection Molding: Experiment and Simulation
  18. Review Paper
  19. State of the Art: Recycling of EPDM Rubber Vulcanizates
  20. PPS News
  21. PPS News
  22. Seikei-Kakou Abstracts
  23. Seikei-Kakou Abstracts
https://doi.org/10.3139/217.0050

Artikel in diesem Heft

  1. Contents
  2. Contents
  3. Regular Contributed Articles
  4. Pressure and Temperature Dependence of LDPE Viscosity and Free Volume: The Effect of Molecular Structure
  5. Correlations between Injection Molding Parameters, Morphology and Mechanical Properties of PPS Using Artificial Neural Networks
  6. Investigations into Kinematic Reversal in Non-isothermal Flows in Single-screw Machines
  7. The Effect of Post-extrusion Conditions in Ribbon Extrusion of Polymer Blends
  8. Effect of the Chemical and Morphological Conditions of the Die Wall on the Extrusion of Linear Polyolefins
  9. Investigation of the Heat Affected Zone of Hot-gas Welded PP Joints
  10. Method for the Optimisation of Screw Elements for Tightly Intermeshing, Co-rotating Twin Screw Extruders
  11. Rheology and Processing of Molten Poly(methyl methacrylate) Resins
  12. PLLA Morphology Controlled by Dry-cast Process
  13. Two Component Injection Molding of Phase Separating Blends
  14. A Low Force Valve for Dynamic Control of Molten Plastics in a Mold
  15. Influence of Drawing and Temperature on the Optical and Structural Properties of Monofilament PP Sutures
  16. Mechanical Properties of Rubber-toughened Post-industrial Glass-fiber-reinforced PA66
  17. Thermal Flow Instability in Metal Injection Molding: Experiment and Simulation
  18. Review Paper
  19. State of the Art: Recycling of EPDM Rubber Vulcanizates
  20. PPS News
  21. PPS News
  22. Seikei-Kakou Abstracts
  23. Seikei-Kakou Abstracts
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