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Research on Angular Variation for Aeroplane-Assembly Base on State Space Model

Variation modeling is one of the most significant tools for assembly variation analysis. Considering dimension and geometric errors, and part situation errors, the error source that affects assembly accuracy is classified into two types: error of geometric location and orientation, error of geometri... Full description

Journal Title: Applied Mechanics and Materials 2013-01-11, Vol.278-280, p.149-154
Main Author: Zhang, Zhi Xiong
Other Authors: Shang, Jian Zhong , Cao, Yu Jun , Li, Xin
Format: Electronic Article Electronic Article
Language: English
Publisher: Zurich: Trans Tech Publications Ltd
ID: ISSN: 1660-9336
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title: Research on Angular Variation for Aeroplane-Assembly Base on State Space Model
format: Article
creator:
  • Zhang, Zhi Xiong
  • Shang, Jian Zhong
  • Cao, Yu Jun
  • Li, Xin
ispartof: Applied Mechanics and Materials, 2013-01-11, Vol.278-280, p.149-154
description: Variation modeling is one of the most significant tools for assembly variation analysis. Considering dimension and geometric errors, and part situation errors, the error source that affects assembly accuracy is classified into two types: error of geometric location and orientation, error of geometric form. And unify these different types of error or deviation by the concept of Virtual Fixture. So a rigid assembly state space model is developed for stream of variation analysis in multi-station assembly processes. And an aeroplane-cabin-assembly process is analyzed in this model. The developed methodology outperforms the current simulation based techniques in computation efficiency, the model is validated using Monte Carlo series Simulations.
language: eng
source:
identifier: ISSN: 1660-9336
fulltext: no_fulltext
issn:
  • 1660-9336
  • 1662-7482
  • 1662-7482
url: Link


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descriptionVariation modeling is one of the most significant tools for assembly variation analysis. Considering dimension and geometric errors, and part situation errors, the error source that affects assembly accuracy is classified into two types: error of geometric location and orientation, error of geometric form. And unify these different types of error or deviation by the concept of Virtual Fixture. So a rigid assembly state space model is developed for stream of variation analysis in multi-station assembly processes. And an aeroplane-cabin-assembly process is analyzed in this model. The developed methodology outperforms the current simulation based techniques in computation efficiency, the model is validated using Monte Carlo series Simulations.
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descriptionVariation modeling is one of the most significant tools for assembly variation analysis. Considering dimension and geometric errors, and part situation errors, the error source that affects assembly accuracy is classified into two types: error of geometric location and orientation, error of geometric form. And unify these different types of error or deviation by the concept of Virtual Fixture. So a rigid assembly state space model is developed for stream of variation analysis in multi-station assembly processes. And an aeroplane-cabin-assembly process is analyzed in this model. The developed methodology outperforms the current simulation based techniques in computation efficiency, the model is validated using Monte Carlo series Simulations.
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notesSelected, peer reviewed papers from the 2012 International Conference on Mechatronics and Control Engineering (ICMCE 2012), November 29-30, 2012, Guangzhou, China
abstractVariation modeling is one of the most significant tools for assembly variation analysis. Considering dimension and geometric errors, and part situation errors, the error source that affects assembly accuracy is classified into two types: error of geometric location and orientation, error of geometric form. And unify these different types of error or deviation by the concept of Virtual Fixture. So a rigid assembly state space model is developed for stream of variation analysis in multi-station assembly processes. And an aeroplane-cabin-assembly process is analyzed in this model. The developed methodology outperforms the current simulation based techniques in computation efficiency, the model is validated using Monte Carlo series Simulations.
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