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Research Papers

Fixture Layout Design of Sheet Metal Parts Based on Global Optimization Algorithms

[+] Author and Article Information
YanFeng Xing

Professor
Mem. ASME
Automobile Engineering College,
Shanghai University of Engineering Science,
Shanghai 201620, China
e-mail: xyf2001721@163.com

1Corresponding author.

Manuscript received January 2, 2017; final manuscript received June 12, 2017; published online August 24, 2017. Assoc. Editor: Ivan Selesnick.

J. Manuf. Sci. Eng 139(10), 101004 (Aug 24, 2017) (10 pages) Paper No: MANU-17-1002; doi: 10.1115/1.4037106 History: Received January 02, 2017; Revised June 12, 2017

Fixture layout can affect deformation and dimensional variation of sheet metal assemblies. Conventionally, the assembly dimensions are simulated with a quantity of finite element (FE) analyses, and fixture layout optimization needs significant user intervention and unaffordable iterations of finite element analyses. This paper therefore proposes a fully automated and efficient method of fixture layout optimization based on the combination of 3dcs simulation (for dimensional analyses) and global optimization algorithms. In this paper, two global algorithms are proposed to optimize fixture locator points, which are social radiation algorithm (SRA) and GAOT, a genetic algorithm (GA) in optimization toolbox in matlab. The flowchart of fixture design includes the following steps: (1) The locating points, the key elements of a fixture layout, are selected from a much smaller candidate pool thanks to our proposed manufacturing constraints based filtering methods and thus the computational efficiency is greatly improved. (2) The two global optimization algorithms are edited to be used to optimize fixture schemes based on matlab. (3) Since matlab macrocommands of 3dcs have been developed to calculate assembly dimensions, the optimization process is fully automated. A case study of inner hood is applied to demonstrate the proposed method. The results show that the GAOT algorithm is more suitable than SRA for generating the optimal fixture layout with excellent efficiency for engineering applications.

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References

Figures

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Fig. 1

Assembly process of sheet metal parts

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Fig. 3

Flowchart of fixture layout design

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Fig. 4

Normal directions of different types of elements

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Fig. 5

Angle between directions of two elements

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Fig. 6

Angle filtering of the bracket part

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Fig. 7

Block and angle definition: (a) locating block of fixture and (b) angle of revolving around one node

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Fig. 8

Boundary filtering of the bracket part (see color figure online)

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Fig. 9

Primary plane filtering of the bracket part (see color figure online)

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Fig. 10

Sparseness filtering

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Fig. 11

Sparseness filtering for the bracket part: (a) 284 candidate points after first sparseness filtering and (b) 92 candidate points after second sparseness filtering

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Fig. 14

Ratio filtering for the bracket part

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Fig. 15

Assembly variation model in 3dcs

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Fig. 16

Ratio curve for bracket part: (a) four locating points in primary plane and (b) ratio curve

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Fig. 18

Flowchart of calculating assembly tolerance by GAOT

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Fig. 19

Optimization process of fixture layout (see color figure online)

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Fig. 20

Case of inner hood part: (a) principle of 4-2-1, (b) four measurement points, and (c) tolerances of four measurement points

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Fig. 21

Candidate points of inner hood

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Fig. 22

Fixture locating schemes of the inner hood part

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