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Tolerance analysis in selective assembly of multiple component features to control assembly variation using matrix model and genetic algorithm

A.K., Jeevanantham and S.V., Chaitanya and Ananthanarayanan, Rajeshkannan (2019) Tolerance analysis in selective assembly of multiple component features to control assembly variation using matrix model and genetic algorithm. International Journal of Precision Engineering and Manufacturing, 20 (10). pp. 1801-1815. ISSN 2234-7593

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    Abstract

    A product may consist of two or more components being assembled together. The geometrical and dimensional tolerances (GDT) present in each feature of the components influence the performance of the assembly. Their accumulation and propagation on assembly fit can be investigated by tolerance analysis. However, during the high precision assembly manufacturing, especially in the selective assembly process, only the dimensional deviations of mating components are considered to evaluate the assembly fit. In this paper, the assembly fits in selective assembly due to GDT of an individual feature of components, is modelled by the matrix method of tolerance analysis. Based on the principles of Technologically and Topologically Related Surfaces and Minimum Geometric Datum Elements, a worst case tolerance analysis is applied into the selective assembly. The conventional method of dividing the components into groups (bins) by dimensional deviation is replaced by integrated GDT. The best combination of components to obtain minimum assembly variation is achieved through a genetic algorithm. The proposed method is demonstrated using a two-dimensional valvetrain assembly that consists of camshaft, tappet, and valve-stem. The effect of considering and annulling the GDT in selective assembly is verified up to 20 numbers of group size.

    Item Type: Journal Article
    Subjects: T Technology > TJ Mechanical engineering and machinery
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
    Depositing User: Rajeshkannan Ananthanarayanan
    Date Deposited: 17 Feb 2020 15:25
    Last Modified: 17 Feb 2020 15:59
    URI: http://repository.usp.ac.fj/id/eprint/11976
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