4.7 Article

A Novel Method for Assemblability Evaluation of Non -Ideal Cylindrical Parts Assembly

期刊

COMPUTER-AIDED DESIGN
卷 134, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.cad.2021.103002

关键词

Assemblability evaluation; Non-ideal surface; Surface deviations; Assembly posture; Assembly clearance

资金

  1. National Natural Science Foundation of China [51575031]
  2. Beijing Municipal Education Commission (Build a Project)

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The paper proposes a novel method for evaluating the assemblability of cylindrical parts assembly considering surface deviations, by simulating the assembly process and defining posture space to achieve quantitative evaluation of assembly posture.
The assemblability, which is the feasibility and difficulty of assembly, will greatly affect the efficiency and quality of assembly process, so assemblability analysis plays an important role during the design stage of products. Cylindrical parts assembly is a common structure with wide applications, whose assemblability can be affected by surface deviations, especially in some precision assemblies. In this paper, a novel method is proposed for the assemblability evaluation of cylindrical parts assembly considering surface deviations. Firstly, based on the surface deviations modeling of cylindrical parts and assembly clearance calculation, the assembly posture adjustment process is defined and simulated to obtain the assemblable postures without interference between parts. Then, in the proposed six dimensional posture space, a search algorithm is established to obtain the boundary points of assemblable posture space. Afterwards, in order to represent this irregular hyperspace, the largest inscribed generalized cone of which is put forward. Finally, based on the characteristics of generalized cone, two indicators are defined to reflect the adjustable range of assembly posture, which can realize the quantitative evaluation of assemblability. The validity of the proposed method is verified by case studies of cylindrical parts assemblies with different surface deviations. (C) 2021 Elsevier Ltd. All rights reserved.

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