Dimensional variation is one of the most critical issues in the design of assembled products. This is especially important for the assembly of compliant, non-rigid parts since clamping and joining during assembly may introduce additional variation due to part deformation and springback. This paper presents a new methodology to predict sheet metal assembly variation using the components geometric covariance. The approach combines the use of principal component analysis and finite element methods to estimate the effect of components variation on assembly variation. Principal component analysis is applied to extract deformation patterns from production data, decomposing the component covariance in the individual contribution of these deformation "modes". Finite element methods are used to determine the effect of each deformation "mode" over the assembly variation. The proposed methodology allows significant reduction in the computation effort required for variation analysis in sheet metal assembly. A ease study is presented to illustrate the methodology.
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