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Tolerance Analysis in Selective Assembly of Multiple Component Features to Control Assembly Variation Using Matrix Model and Genetic Algorithm

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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.

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Authors and Affiliations

  1. School of Mechanical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India

    A. K. Jeevanantham & S. V. Chaitanya

  2. Department of Mechanical Engineering, FSTE, SEP, The University of the South Pacific, Laucala Campus, Suva, Fiji

    A. Rajeshkannan

Authors
  1. A. K. Jeevanantham
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  2. S. V. Chaitanya
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  3. A. Rajeshkannan
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Correspondence to A. K. Jeevanantham.

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Jeevanantham, A.K., Chaitanya, S.V. & Rajeshkannan, A. Tolerance Analysis in Selective Assembly of Multiple Component Features to Control Assembly Variation Using Matrix Model and Genetic Algorithm. Int. J. Precis. Eng. Manuf. 20, 1801–1815 (2019). https://doi.org/10.1007/s12541-019-00194-x

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  • DOI: https://doi.org/10.1007/s12541-019-00194-x

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