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3-D Fixture Layout Design System Based on Genetic Algorithm

Yeung, Ka Yiu and Chen, Xun (2010) 3-D Fixture Layout Design System Based on Genetic Algorithm. Proceedings of the 16th International conference on Automation & Computing. pp. 238-243. ISSN 9780955529368

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Abstract

Designing a fixture layout is the primary task of fixture design, which consists of determining the different combinations of locators and clamping scheme. Designing a fixture is a lengthy process and the performance of a fixture is usually difficult to predict. Designing fixture to effectively restrain complex components has been recognised as a bottleneck in fixture design development. The aim of this research is to develop a genetic algorithm (GA) based methodology to support effective fixture layout optimization for 3-D component. Reduce the dependence on designers expertise to deliver the fixture layout design against his/her own particular design methodology. Efforts of the application are focused on optimisation of the positions of locators and clamps for complex geometry components, such as a turbine blade. Overall, results suggest the feasibly of using GA in fixturing layout optimization.

Item Type: Article
Additional Information: Paper presented at the 16th International Cinference on Automation and Computing (ICAC'10), Birmingham, UK, 11th September 2010
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > TJ Mechanical engineering and machinery
T Technology > TS Manufactures
Schools: School of Computing and Engineering
School of Computing and Engineering > Centre for Precision Technologies
School of Computing and Engineering > Centre for Precision Technologies > Advanced Machining Technology Group
School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
School of Computing and Engineering > Diagnostic Engineering Research Centre
School of Computing and Engineering > High-Performance Intelligent Computing
Depositing User: Xun Chen
Date Deposited: 05 Oct 2010 13:13
Last Modified: 10 Dec 2010 09:20
URI: http://eprints.hud.ac.uk/id/eprint/8746

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