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Research Papers

Variation Simulation of Stresses Using the Method of Influence Coefficients

[+] Author and Article Information
Samuel Lorin

e-mail: samuel.lorin@chalmers.se

Lars Lindkvist

e-mail: lali@chalmers.se

Rikard Söderberg

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

1Corresponding author.

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINNERING. Manuscript received August 22, 2013; final manuscript received September 24, 2013; published online November 14, 2013. Editor: Bahram Ravani.

J. Comput. Inf. Sci. Eng 14(1), 011001 (Nov 14, 2013) (7 pages) Paper No: JCISE-13-1162; doi: 10.1115/1.4025632 History: Received August 22, 2013; Revised September 24, 2013

In every manufacturing situation there are geometric deviations leading to variation in properties of the manufactured products. Variation affects the manufacturability, functions and aesthetics of the products. Therefore, a number of methods and tools have been developed during the last 20 yr in order to assure the geometric quality and to minimize the effect of variability. These methods and tools have mainly been developed for rigid- or sheet metal components. Plastics or composites have been an increasingly popular material due to their flexible mechanical properties and their relative ease in manufacturing. However, their mechanical properties are introducing challenges that have not often been addressed in the process of geometry assurance. One challenge is to assure that the stresses introduced, as a consequence of non-nominal assembly, are kept well below critical limits during the conditions of use. In this paper, we are proposing the use of the method of influence coefficients (MIC) to simulate the distribution of von Mises stresses in assembled components. This method will be compared to the more flexible but computationally much heavier direct Monte Carlo (DMC) method, which is not suitable for variation simulation due to the large number of runs required for statistical inference. Two industrial case studies are presented to elicit the need of the proposed method.

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Topics: Simulation , Stress
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Figures

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Fig. 1

Relations between displacements, strains, and stresses

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Fig. 2

The positioning system for the component used for comparing DMC and MIC. The red arrows denote the 3–2–1 positioning system and the two blue arrows denote the 2 support points

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Fig. 3

The von Mises stress in the 4 points implied by the arrows is recorded for DMC and MIC

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Fig. 4

Comparison between DMC and MIC for von Mises stress in four measures (MPa)

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Fig. 5

A plastic appliqué (in blue) and the corresponding positioning system

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Fig. 6

Color-coding of the mean values of the induced von Mises Stresses (MPa)

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Fig. 7

Color-coding of the 6 standard deviations of von Mises Stresses (MPa)

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Fig. 8

The position of 3 measures used to record the distribution of von Mises Stresses

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Fig. 9

The distributions of measure 1–3 from case study 1

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Fig. 10

In case 2, the appliqué is hindered to expand with temperature along the y-direction by locking the positioned appliqué in the y-direction in the positions indicated by the circles

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Fig. 11

The distributions of measure 1–3 from case study 2 in −30  °C

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Fig. 12

The distributions of measure 1–3 from case study 2 in 60  °C

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