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Research Papers

Method for Handling Model Growth in Nonrigid Variation Simulation of Sheet Metal Assemblies

[+] Author and Article Information
Björn Lindau

Department 81720,
Geopl. PVÖE 101,
Volvo Cars,
Göteborg SE-405 31, Sweden
e-mail: bjorn.lindau@volvocars.com

Kristina Wärmefjord

Mem. ASME
Product and Production
Development Department,
Chalmers University of Technology,
Göteborg SE-412 96, Sweden
e-mail: kristina.warmefjord@chalmers.se

Lars Lindkvist

Associate Professor
Product and Production
Development Department,
Chalmers University of Technology,
Göteborg SE-412 96, Sweden
e-mail: lali@chalmers.se

Rikard Söderberg

Professor
Mem. ASME
Product and Production
Development Department,
Chalmers University of Technology,
Göteborg SE-412 96, Sweden
e-mail: rikard.soderberg@chalmers.se

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received February 4, 2014; final manuscript received February 18, 2014; published online April 28, 2014. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 14(3), 031004 (Apr 28, 2014) (12 pages) Paper No: JCISE-14-1041; doi: 10.1115/1.4027149 History: Received February 04, 2014; Revised February 18, 2014

In automotive industry, virtual tools and methods are becoming increasingly important to ensure robust solutions as early as possible in the development processes. Today, techniques exist that combine Monte Carlo simulations (MCS) with finite element analysis (FEA) to capture the part's nonrigid geometric behavior when predicting variation in a critical dimension of a subassembly or product. A direct combination of MCS with full FEA requires high computational power and the calculations tend to be very time consuming. To overcome this problem, the method of influence coefficients (MIC) was proposed by Liu and Hu in the late 1990s. This well-known technique has since then been used in several studies of nonrigid assemblies and sensitivity analysis of the geometric fault propagation in multistation assembly processes. In detailed studies of the resulting subassemblies and levels of variation, functionality for color plots and the ability to study the geometry in arbitrary sections are desired to facilitate the analysis of the simulation results. However, when including all part nodes in combination with methods for contact and spot weld sequence modeling, the required sensitivity matrices grow exponentially. In this paper, a method is proposed, describing how traditional MIC calculations can be combined with a separate detailed subassembly analysis model, keeping the model sizes down and thus facilitating detailed studies of larger assembly structures.

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References

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Figures

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Fig. 1

Example of a color plot and section analysis in RD&T

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Fig. 2

Compliant module using sequential datasets as input

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Fig. 3

Analysis module using sequential datasets as input

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Fig. 4

Compliant module using PCA representation as input

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Fig. 5

Analysis module using PCA representation as input

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Fig. 6

Locating scheme for the wheel house assembly

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Fig. 9

Color plots showing full simulation and analysis modeling, unit mm

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Fig. 10

Difference between full simulation and analysis model, unit mm

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Fig. 11

Cumulative percentage of total variation

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