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
- Injection Molding Design
- Defect Prediction in Injection Molding
- Gate Systems for Scrap Reduction
- Gate Design Optimization
- Cold Runner Design
- Plastic Defects Analysis
- Filling Process Analysis
- Fuzzy Optimization in Manufacturing
- Taguchi Experimental Design
- Process Optimization via Fuzzy AHP
- Application of Fuzzy TOPSIS
- Combination of ANOVA and Taguchi Methods
About this book
Authors and Affiliations
Bibliographic Information
Book Title: Intelligent Optimization of Mold Design and Process Parameters in Injection Molding
Authors: Mehdi Moayyedian
Series Title: Springer Theses
DOI: https://doi.org/10.1007/978-3-030-03356-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-03355-2Published: 13 November 2018
eBook ISBN: 978-3-030-03356-9Published: 02 November 2018
Series ISSN: 2190-5053
Series E-ISSN: 2190-5061
Edition Number: 1
Number of Pages: XXII, 145
Number of Illustrations: 22 b/w illustrations, 80 illustrations in colour
Topics: Manufacturing, Machines, Tools, Processes, Engineering Design, Computational Intelligence, Numerical and Computational Physics, Simulation