Fixture layout can affect deformation and dimensional variation of sheet metal assemblies. Conventionally, the assembly dimensions are simulated using a large number of finite element analyses, and fixture layout optimization needs significant user intervention and unaffordable iterations of finite element analyses. This paper therefore proposes a fully automated and efficient method of fixture layout optimization based on the combination of 3DCS simulation (for dimensional analyses) and GAOT, a genetic algorithm in optimization toolbox in MATLAB. The locating points, the key elements of a fixture layout, are selected from a much smaller candidate pool thanks to our proposed manufacturing constraints based filtering methods and thus the computational efficiency is greatly improved. Since MATLAB macro commands of 3DCS have been developed to calculate assembly dimensions, the optimization process is fully automated. A case study of inner hood is applied to demonstrate the proposed method. The results show that the proposed method is suitable for generating the optimal fixture layout with excellent efficiency for engineering applications.
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ASME 2016 International Mechanical Engineering Congress and Exposition
November 11–17, 2016
Phoenix, Arizona, USA
Conference Sponsors:
- ASME
ISBN:
978-0-7918-5052-7
PROCEEDINGS PAPER
Fixture Layout Design and Optimization of Sheet Metal Assembly Based on Genetic Algorithm for Optimization Toolbox
Yanfeng Xing,
Yanfeng Xing
Shanghai University of Engineering Science, Shanghai, China
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Fang Wang,
Fang Wang
Shanghai University of Engineering Science, Shanghai, China
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Qing Ji
Qing Ji
Shanghai University of Engineering Science, Shanghai, China
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Yanfeng Xing
Shanghai University of Engineering Science, Shanghai, China
Fang Wang
Shanghai University of Engineering Science, Shanghai, China
Qing Ji
Shanghai University of Engineering Science, Shanghai, China
Paper No:
IMECE2016-65413, V002T02A018; 7 pages
Published Online:
February 8, 2017
Citation
Xing, Y, Wang, F, & Ji, Q. "Fixture Layout Design and Optimization of Sheet Metal Assembly Based on Genetic Algorithm for Optimization Toolbox." Proceedings of the ASME 2016 International Mechanical Engineering Congress and Exposition. Volume 2: Advanced Manufacturing. Phoenix, Arizona, USA. November 11–17, 2016. V002T02A018. ASME. https://doi.org/10.1115/IMECE2016-65413
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