Application of robust design optimization to extrusion slit die design

  • Authors:

  • S. J. Bates;J. Sienz;J. F. T. Pittman;D. S. Langley

  • Affiliations:

  • Centre for Polymer Processing Simulation & Design and ADOPT research group, Civil and Computational Engineering, School of Engineering, University of Wales, Swansea, United Kingdom;Centre for Polymer Processing Simulation & Design and ADOPT research group, Civil and Computational Engineering, School of Engineering, University of Wales, Swansea, United Kingdom;Centre for Polymer Processing Simulation & Design and ADOPT research group, Civil and Computational Engineering, School of Engineering, University of Wales, Swansea, United Kingdom;Centre for Polymer Processing Simulation & Design and ADOPT research group, Civil and Computational Engineering, School of Engineering, University of Wales, Swansea, United Kingdom

  • Venue:
  • ICECT'03 Proceedings of the third international conference on Engineering computational technology
  • Year:
  • 2002

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Abstract

Based on a simulation of slit die performance that takes into account the coupling of melt flow and die body deflection due to melt pressure, a Genetic Algorithm (GA) is used to determine choker bar profiles to give optimum (ideally uniform) melt flow distribution. The deterministic solution gained using conventional optimization alone is not necessarily a robust solution, i.e. scatter caused by slight changes in uncontrollable noise factors such as the input flow rate of the polymer or the operating temperatures may cause dramatic non-uniformity in the melt flow distribution. A GA is used to achieve a robust design by solving a bi-objective problem that minimizes both the original objective function and the variation caused by scatter. This paper compares the optimum found without robustness considerations to those gained using the physical programming (PP) method [1] to generate the Pareto set for the bi-objective problem.