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IJAT Vol.17 No.2 pp. 167-175
doi: 10.20965/ijat.2023.p0167
(2023)

Research Paper:

Automated Generation of Product Assembly Order Based on Geometric Constraints Between Parts

Isamu Nishida*,†, Hayato Sawada**, and Keiichi Shirase*

*Kobe University
1-1 Rokko-dai, Nada-ku, Kobe, Hyogo 657-8501, Japan

Corresponding author

**Yanmar Holdings Co., Ltd.
Amagasaki, Japan

Received:
July 14, 2022
Accepted:
September 8, 2022
Published:
March 5, 2023
Keywords:
automated product assembly, disassembly, assembly order, CAD
Abstract

This study proposes a method for automating the determination of assembly order by automating the derivation of the necessary connection relationships between the parts. The proposed method minimizes the information required for the initial conditions and automatically determines the feasible assembly orders. As a general rule, based on the assumption that the assembly order for a product is the reverse of the disassembly order, once the disassembly order is derived based on the 3D CAD model and the connection relationships between the parts, the assembly order can be determined. Until now, however, the relationships between the parts are decided manually by the attendant engineers, thus, hindering the full automation of the determination of the assembly order. To achieve full automation realistically, the connection relationships between the parts should be derived automatically from the 3D CAD model, for which this study proposes an efficient method. The components were extracted from the 3D CAD model, and the bolts were identified. The connection relationships between the parts were derived from the interference conditions determined while moving each part minutely. An association chart diagram was created from the obtained connection relationships, from which multiple assembly order candidates could be derived.

Cite this article as:
I. Nishida, H. Sawada, and K. Shirase, “Automated Generation of Product Assembly Order Based on Geometric Constraints Between Parts,” Int. J. Automation Technol., Vol.17 No.2, pp. 167-175, 2023.
Data files:
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Last updated on Jul. 12, 2024