Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/16854
Title: An intelligent hybrid system for initial process parameter setting of injection moulding
Authors: Mok, SL
Kwong, CK 
Lau, WS
Issue Date: 2000
Source: International journal of production research, 2000, v. 38, no. 17, p. 4565-4576
Abstract: Currently, determination of the initial process parameter settings for injection moulding is mainly performed by moulding personnel, and the effectiveness of the parameter setting is largely dependent on the experience of these personnel. In this paper, an intelligent hybrid system, called HSIM, is described, which is used to determine a set of initial process parameters for injection moulding based on the artificial intelligence (AI) techniques, case-based reasoning (CBR), and hybrid neural network (NN) and genetic algorithm (GA). HSIM can determine a set of initial process parameters for injection moulding quickly, without relying on expert moulding personnel, from which moulded parts free from major moulding defects can be produced.
Publisher: Taylor & Francis
Journal: International journal of production research 
ISSN: 0020-7543
EISSN: 1366-588X
DOI: 10.1080/00207540050205307
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