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Intelligent Optimization of Mold Design and Process Parameters in Injection Molding

  • Book
  • © 2019

Overview

  • Nominated as an outstanding PhD thesis by University of South Australia, Adelaide, Australia
  • Describes experimental, numerical and optimization techniques for improving mold design
  • Demonstrates the efficacy of combining different methods, such as ANOVA, Taguchi, TOPSIS and fuzzy logic
  • Offers a comprehensive review on injection modeling process and mold design concepts

Part of the book series: Springer Theses (Springer Theses)

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Table of contents (7 chapters)

Keywords

About this book

This book describes an effective framework for setting the right process parameters and new mold design to reduce the current plastic defects in injection molding. It presents a new approach for the optimization of injection molding process via (i) a new mold runner design which leads to 20 percent reduction in scrap rate, 2.5 percent reduction in manufacturing time, and easier ejection of injected part, (ii) a new mold gate design which leads to less plastic defects; and (iii) the introduction of a number of promising alternatives with high moldability indices. Besides presenting  important developments of relevance academic research, the book also includes useful information for people working in the injection molding industry, especially in the green manufacturing field.

Authors and Affiliations

  • School of Engineering, University of South Australia, Adelaide, Australia

    Mehdi Moayyedian

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