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
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: 1468-0394
DOI: 10.1111/j.1468-0394.2005.00289.x
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