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Online Wall Thickness Control for Blow Molded Part Using Hybrid Optimization Method and Fuzzy Iterative Learning Control Algorithm

[+] Author Affiliations
Geng-Qun Huang, Han-Xiong Huang

South China University of Technology, Guangzhou, China

Paper No. IMECE2008-68292, pp. 445-451; 7 pages
  • ASME 2008 International Mechanical Engineering Congress and Exposition
  • Volume 10: Heat Transfer, Fluid Flows, and Thermal Systems, Parts A, B, and C
  • Boston, Massachusetts, USA, October 31–November 6, 2008
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4871-5 | eISBN: 978-0-7918-3840-2
  • Copyright © 2008 by ASME


An online wall thickness control strategy for the extrusion blow molded part was proposed in this work. A simulation-based optimization method combining with finite element, artificial neural network, and genetic algorithm was used to determine the initial die gap profile for a part with required thickness distribution. A multi-channel ultrasonic thickness measurement system was built up to get the in-mold wall thickness of the blow molded part. Then, a feedback closed-loop control system based on fuzzy iterative learning control algorithm was designed and implemented to control the wall thickness of blow molded part. The results showed that the online wall thickness control system developed in this work can automatically achieve a proper die gap profile and get the satisfied part thickness distribution.

Copyright © 2008 by ASME



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