Design optimization of the blow moulding process using a fuzzy optimization algorithm

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1243/095440504322886523
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  1. National Research Council Canada
FormatText
TypeArticle
Journal titleProceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
ISSN0954-4054
2041-2975
Volume218
Issue2
Pages197–212
Abstract
Blow moulding is the forming of a hollow part by ‘blowing’ a mould cavity shaped parison made by a thermoplastic molten tube. Blow-moulded parts often require strict control of the thickness distribution in order to achieve the required mechanical performance and final weight. A fuzzy optimization algorithm for determining the optimal die gap openings and die geometry for the required thickness distribution in the blow moulding process is presented. The idea of the fuzzy optimization algorithm is that, instead of using purely numerical information to obtain the new design point in the next iteration, engineering knowledge and the human supervision process can be modelled in the optimization algorithm using fuzzy rules. The structure of an optimization algorithm is still maintained to guide the engineering decision process and to ensure that an optimal solution rather than a trial and error solution can be obtained. It is shown how a single fuzzy engine can be used in various cases and types of optimization of the blow moulding process.
Publication date
PublisherSAGE
LanguageEnglish
Peer reviewedYes
NPARC number23001676
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Record identifier912b863c-fdf4-4c57-90b9-b027a2059833
Record created2017-03-16
Record modified2017-03-16
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