A novel algorithm of posture best fit based on key characteristics for large components assembly

Lianyu Zheng*, Xusheng Zhu, Renwei Liu, Yiwei Wang, Paul G. Maropoulos

*Corresponding author for this work

    Research output: Contribution to journalArticle

    Abstract

    Measurement and variation control of geometrical Key Characteristics (KCs), such as flatness and gap of joint faces, coaxiality of cabin sections, is the crucial issue in large components assembly from the aerospace industry. Aiming to control geometrical KCs and to attain the best fit of posture, an optimization algorithm based on KCs for large components assembly is proposed. This approach regards the posture best fit, which is a key activity in Measurement Aided Assembly (MAA), as a two-phase optimal problem. In the first phase, the global measurement coordinate system of digital model and shop floor is unified with minimum error based on singular value decomposition, and the current posture of components being assembly is optimally solved in terms of minimum variation of all reference points. In the second phase, the best posture of the movable component is optimally determined by minimizing multiple KCs' variation with the constraints that every KC respectively conforms to its product specification. The optimal models and the process procedures for these two-phase optimal problems based on Particle Swarm Optimization (PSO) are proposed. In each model, every posture to be calculated is modeled as a 6 dimensional particle (three movement and three rotation parameters). Finally, an example that two cabin sections of satellite mainframe structure are being assembled is selected to verify the effectiveness of the proposed approach, models and algorithms. The experiment result shows the approach is promising and will provide a foundation for further study and application. © 2013 The Authors.

    Original languageEnglish
    Pages (from-to)162-168
    Number of pages7
    JournalProcedia CIRP
    Volume10
    Early online date19 Sep 2013
    DOIs
    Publication statusPublished - 2013
    Event12th CIRP conference on Computer Aided Tolerancing - Huddersfield, United Kingdom
    Duration: 18 Apr 201219 Apr 2012

    Bibliographical note

    © 2013 The Authors. Published by Elsevier B.V. Open access under CC BY-NC-ND license.

    12th CIRP Conference on Computer Aided Tolerancing

    Keywords

    • best fit
    • key characteristics
    • large volume metrology
    • measurement aided assembly
    • posture
    • KCs
    • LVM
    • MAA

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