In this paper, the SVA-FEA (Statistical Variation Analysis & Finite Element Analysis) method to do tolerance/variation analysis of multi-station assemblies of compliant parts is presented. Based mainly on the 'unit displacement' and 'sensitivity matrix' method, the proposed method allows for the use of statistical variation data in the fixturing and fastening points to predict the final shape variation of multi-station assembly systems. 'Linear' contacts between compliant parts is also included to model in more real fashion the spring-back effect between mating parts. So what happens at the end of the assembly process may be predicted. This evaluation enables users to analyze different assembly configurations in the early design phase. The implementation of the proposed method has provided a new Matlab-based variation analysis tool. For each assembly station only two FEA runs are required. No Monte Carlo simulation is needed. Finally, two case studies are presented and discussed.
Statistical variation analysis of multi-station compliant assemblies based on sensitivity matrix / Gerbino, S.; Patalano, Stanislao; Franciosa, Pasquale. - In: INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY. - ISSN 0952-8091. - STAMPA. - 33:1(2008), pp. 12-23.
Statistical variation analysis of multi-station compliant assemblies based on sensitivity matrix
PATALANO, STANISLAO;FRANCIOSA, PASQUALE
2008
Abstract
In this paper, the SVA-FEA (Statistical Variation Analysis & Finite Element Analysis) method to do tolerance/variation analysis of multi-station assemblies of compliant parts is presented. Based mainly on the 'unit displacement' and 'sensitivity matrix' method, the proposed method allows for the use of statistical variation data in the fixturing and fastening points to predict the final shape variation of multi-station assembly systems. 'Linear' contacts between compliant parts is also included to model in more real fashion the spring-back effect between mating parts. So what happens at the end of the assembly process may be predicted. This evaluation enables users to analyze different assembly configurations in the early design phase. The implementation of the proposed method has provided a new Matlab-based variation analysis tool. For each assembly station only two FEA runs are required. No Monte Carlo simulation is needed. Finally, two case studies are presented and discussed.File | Dimensione | Formato | |
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