Variation Simulation of Sheet Metal Assemblies Using the Method of Influence Coefficients With Contact Modeling

[+] Author and Article Information
Stefan Dahlström

 Volvo Car Corporation, BIW Structure Engineering, Department 93740, Loc. PV2A, SE-405 31 Göteborg, Swedensdahlstr@volvocars.com

Lars Lindkvist

Department of Product and Production Development, Chalmers University of Technology, SE-412 96 Göteborg, Sweden

J. Manuf. Sci. Eng 129(3), 615-622 (Nov 13, 2006) (8 pages) doi:10.1115/1.2714570 History: Received March 11, 2005; Revised November 13, 2006

Sheet metal assembly is a common assembly process for several products such as automobiles and airplanes. Since all manufacturing processes are affected by variation, and products need to have a high geometric quality, geometry-related production problems must be analyzed during early design phases. This paper discusses two methods of performing this analysis. One way of performing the simulations relatively fast is to establish linear relationships between part deviation and assembly springback deviation by using the method of influence coefficient (MIC). However, this method does not consider contact between the parts. This means that the parts are allowed to penetrate each other which can affect the accuracy of the simulation result. This paper presents a simple contact modeling technique that can be implemented in to MIC to avoid penetrations. The contact modeling consists of a contact detection and a contact equilibrium search algorithm. When implemented, MIC still only requires two finite element analysis (FEA) calculations. This paper describes the steps in the contact algorithm and how it can be used in MIC, and finally the proposed contact modeling is verified by comparing the simulation result with commercial FEA software ABAQUS contact algorithm.

Copyright © 2007 by American Society of Mechanical Engineers
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Figure 1

Method of influence coefficient

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Figure 2

Vertex sense of a triangle

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Figure 3

Force and moment equilibrium over elements

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Figure 4

Algorithm for solving Eq. 4

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Figure 5

MIC with contact modeling

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Figure 6

Geometry and constraint of the simulation example

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Figure 7

Node numbering of the simulation example

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Figure 8

Comparison DMC and MIC without contact

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Figure 9

Comparison DMC with and without contact

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Figure 10

Comparison DMC and MIC with contact modeling




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