Conference Agenda
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GEOM: Geometric Modeling & Processing Location: B8.1.2 Session Chair: Prof. Domenico Marzullo, university of Trieste Session Chair: Dr. Francesco Buonamici, University of Florence | |
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Data-Driven Parametric CAD Modeling of Geometric Variability with Correlated Variables 1: Laboratory of Design Methods and Tools in Industrial Engineering, Department of Civil, Environmental and Architectural Engineering, University of Padova, Via Venezia 1, 35131 Padova Italy; 2: Department of Industrial Engineering, Via Venezia 1, 35131, Padova, Italy; 3: Department of Management and Engineering, University of Padova, Stradella San Nicola 3, 36100 Vicenza Italy This paper proposes a statistical CAD modeling framework to generate par-ametric geometries representative of manufacturing variability based on measurement data. The method combines distribution fitting and percentile-based modeling of design variables with correlation information to reproduce realistic relationships among geometric parameters. In contrast with Principal Component Analysis approaches, the proposed framework preserves the original CAD design variables, preserving the physical interpretability of the original CAD design variables and enabling direct interpretation. The meth-odology is implemented through an automated workflow that generates sta-tistically consistent CAD instances by propagating deviations according to the extracted correlation matrix. A case study on a machined component is presented to demonstrate the capability of the approach to capture process-dependent variability and correlated behavior among parameters. The results confirm that the proposed method can generate statistically representative CAD models suitable for simulation-driven analyzes. | |