Fuzzy control on manufacturing welding systems: To apply fuzzy theory in the control of weld line of plastic injection-molding

Mei Yung Chen, Yi Cheng Chen, Shia Chung Chen

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The present study has successfully applied fuzzy control logic in controlling the weld line position for an injection-molded part. Although only a simple molded part was dealt with here, the incorporation of fuzzy control with CAE software in controlling the weld line position is a breakthrough in the concept of mold-design optimization. During the analysis, only four calculations of decision and simulation were conducted before the final result was obtained, saving considerable time compared with conventional trial and error or computer simulation methods. Consequently, the mold-design process can be accelerated. Since the weld line does appear at the expected location in the actual molded part, the present results can provide a sound basis for developing mold-design optimization. Future works under consideration include: 1)Apply the present approach to molded parts with complex geometry.2)Apply the present approach to molded parts with two or more gates, i.e., two or more output variables are necessary, as IF E is MP and V is NP, THEN U1 is SP and U2 is NP 3)Membership functions and some rules are established by neural networks so as to reduce manual input.

Original languageEnglish
Title of host publicationAdvances in Industrial Control
PublisherSpringer International Publishing
Pages315-324
Number of pages10
Edition9781846284687
DOIs
Publication statusPublished - 2006 Jan 1

Publication series

NameAdvances in Industrial Control
Number9781846284687
ISSN (Print)1430-9491
ISSN (Electronic)2193-1577

Fingerprint

Plastics molding
Fuzzy control
Injection molding
Welding
Welds
Computer aided engineering
Membership functions
Acoustic waves
Neural networks
Computer simulation
Design optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Automotive Engineering
  • Aerospace Engineering
  • Industrial and Manufacturing Engineering

Cite this

Chen, M. Y., Chen, Y. C., & Chen, S. C. (2006). Fuzzy control on manufacturing welding systems: To apply fuzzy theory in the control of weld line of plastic injection-molding. In Advances in Industrial Control (9781846284687 ed., pp. 315-324). (Advances in Industrial Control; No. 9781846284687). Springer International Publishing. https://doi.org/10.1007/978-1-84628-469-4_21

Fuzzy control on manufacturing welding systems : To apply fuzzy theory in the control of weld line of plastic injection-molding. / Chen, Mei Yung; Chen, Yi Cheng; Chen, Shia Chung.

Advances in Industrial Control. 9781846284687. ed. Springer International Publishing, 2006. p. 315-324 (Advances in Industrial Control; No. 9781846284687).

Research output: Chapter in Book/Report/Conference proceedingChapter

Chen, MY, Chen, YC & Chen, SC 2006, Fuzzy control on manufacturing welding systems: To apply fuzzy theory in the control of weld line of plastic injection-molding. in Advances in Industrial Control. 9781846284687 edn, Advances in Industrial Control, no. 9781846284687, Springer International Publishing, pp. 315-324. https://doi.org/10.1007/978-1-84628-469-4_21
Chen MY, Chen YC, Chen SC. Fuzzy control on manufacturing welding systems: To apply fuzzy theory in the control of weld line of plastic injection-molding. In Advances in Industrial Control. 9781846284687 ed. Springer International Publishing. 2006. p. 315-324. (Advances in Industrial Control; 9781846284687). https://doi.org/10.1007/978-1-84628-469-4_21
Chen, Mei Yung ; Chen, Yi Cheng ; Chen, Shia Chung. / Fuzzy control on manufacturing welding systems : To apply fuzzy theory in the control of weld line of plastic injection-molding. Advances in Industrial Control. 9781846284687. ed. Springer International Publishing, 2006. pp. 315-324 (Advances in Industrial Control; 9781846284687).
@inbook{9fa8b91c9d9740df98927f95868cb3e2,
title = "Fuzzy control on manufacturing welding systems: To apply fuzzy theory in the control of weld line of plastic injection-molding",
abstract = "The present study has successfully applied fuzzy control logic in controlling the weld line position for an injection-molded part. Although only a simple molded part was dealt with here, the incorporation of fuzzy control with CAE software in controlling the weld line position is a breakthrough in the concept of mold-design optimization. During the analysis, only four calculations of decision and simulation were conducted before the final result was obtained, saving considerable time compared with conventional trial and error or computer simulation methods. Consequently, the mold-design process can be accelerated. Since the weld line does appear at the expected location in the actual molded part, the present results can provide a sound basis for developing mold-design optimization. Future works under consideration include: 1)Apply the present approach to molded parts with complex geometry.2)Apply the present approach to molded parts with two or more gates, i.e., two or more output variables are necessary, as IF E is MP and V is NP, THEN U1 is SP and U2 is NP 3)Membership functions and some rules are established by neural networks so as to reduce manual input.",
author = "Chen, {Mei Yung} and Chen, {Yi Cheng} and Chen, {Shia Chung}",
year = "2006",
month = "1",
day = "1",
doi = "10.1007/978-1-84628-469-4_21",
language = "English",
series = "Advances in Industrial Control",
publisher = "Springer International Publishing",
number = "9781846284687",
pages = "315--324",
booktitle = "Advances in Industrial Control",
edition = "9781846284687",

}

TY - CHAP

T1 - Fuzzy control on manufacturing welding systems

T2 - To apply fuzzy theory in the control of weld line of plastic injection-molding

AU - Chen, Mei Yung

AU - Chen, Yi Cheng

AU - Chen, Shia Chung

PY - 2006/1/1

Y1 - 2006/1/1

N2 - The present study has successfully applied fuzzy control logic in controlling the weld line position for an injection-molded part. Although only a simple molded part was dealt with here, the incorporation of fuzzy control with CAE software in controlling the weld line position is a breakthrough in the concept of mold-design optimization. During the analysis, only four calculations of decision and simulation were conducted before the final result was obtained, saving considerable time compared with conventional trial and error or computer simulation methods. Consequently, the mold-design process can be accelerated. Since the weld line does appear at the expected location in the actual molded part, the present results can provide a sound basis for developing mold-design optimization. Future works under consideration include: 1)Apply the present approach to molded parts with complex geometry.2)Apply the present approach to molded parts with two or more gates, i.e., two or more output variables are necessary, as IF E is MP and V is NP, THEN U1 is SP and U2 is NP 3)Membership functions and some rules are established by neural networks so as to reduce manual input.

AB - The present study has successfully applied fuzzy control logic in controlling the weld line position for an injection-molded part. Although only a simple molded part was dealt with here, the incorporation of fuzzy control with CAE software in controlling the weld line position is a breakthrough in the concept of mold-design optimization. During the analysis, only four calculations of decision and simulation were conducted before the final result was obtained, saving considerable time compared with conventional trial and error or computer simulation methods. Consequently, the mold-design process can be accelerated. Since the weld line does appear at the expected location in the actual molded part, the present results can provide a sound basis for developing mold-design optimization. Future works under consideration include: 1)Apply the present approach to molded parts with complex geometry.2)Apply the present approach to molded parts with two or more gates, i.e., two or more output variables are necessary, as IF E is MP and V is NP, THEN U1 is SP and U2 is NP 3)Membership functions and some rules are established by neural networks so as to reduce manual input.

UR - http://www.scopus.com/inward/record.url?scp=85021182589&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85021182589&partnerID=8YFLogxK

U2 - 10.1007/978-1-84628-469-4_21

DO - 10.1007/978-1-84628-469-4_21

M3 - Chapter

AN - SCOPUS:85021182589

T3 - Advances in Industrial Control

SP - 315

EP - 324

BT - Advances in Industrial Control

PB - Springer International Publishing

ER -