Tolerance Analysis of a Deformable Component Using the Probabilistic Approach and Kriging-Based Surrogate Models

Abstract

Tolerance analysis is a key issue in proving the compatibility of manufacturing uncertainties with the quality level of mechanical systems. For rigid and isostatic systems, multiple methods (worst case, statistical, or probabilistic approaches) are applicable and well established. Recent scientific developments have brought enhancements for rigid overconstrained systems using probabilistic and optimization-based methods. The consideration of nonrigid systems is more complex since a large-scale numerical model must be taken into account for an accurate prediction of the quality. The aim of the present paper is the illustration of the probabilistic tolerance analysis approach for an industrial application involving deformable parts. The distributions associated with the dimensions of the components were identified using real components collected from the assembly lines. A nonlinear finite-element model was used to predict the mechanical behavior. A reliability analysis was performed in order to compute the defect probability and estimate the quality of the products. A kriging-based surrogate model was used to reduce the numerical efforts required for the reliability analysis.