Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34580
Title: Design and implementation of a process optimizer : a case study on monitoring molding operations
Authors: Lau, HC
Lee, CKM
Ip, WH 
Chan, FT
Leung, RW
Keywords: Fuzzy logic reasoning
Genetic algorithm
Artificial intelligence
Optimization
Issue Date: 2005
Publisher: Wiley-Blackwell
Source: Expert systems, 2005, v. 22, no. 1, p. 12-21 How to cite?
Journal: Expert systems 
Abstract: To cope with the requirements of high dimensional accuracy for injection molding components, it is important to optimize the process parameters in order to sustain the high level dimensional quality of the molded parts. In this respect, a study in the domain of process optimization is of paramount importance in terms of determining the optimal set of injection molding parameters. To this end, a methodology to establish an integrated model which consists of both fuzzy logic reasoning and a genetic algorithm is proposed. These two artificial intelligence techniques can complement each other to form an integrated model which capitalizes on the merits and at the same time offsets the pitfalls of the involved technologies. To validate the feasibility of the proposed model, a case study related to injection molding optimization is also covered in this paper.
URI: http://hdl.handle.net/10397/34580
ISSN: 0266-4720
EISSN: 1468-0394
DOI: 10.1111/j.1468-0394.2005.00289.x
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

WEB OF SCIENCETM
Citations

9
Last Week
0
Last month
Citations as of Sep 15, 2017

Page view(s)

30
Last Week
0
Last month
Checked on Sep 18, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.