سال انتشار: ۱۳۸۶
محل انتشار: هفتمین همایش انجمن هوافضای ایران
تعداد صفحات: ۹
Behnam Moetakef-Imani – Department of Mechanical Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Assistant Professor
Seyed-Ali Hashemian – M.Sc. Student of Mechanical Enginnering
Statistical tolerance alalysis (STA) has an essentail role to associate product design with manufacturing, aiding to increase quality, while lowering production costs. Conventional tolerance analysis methods are limited by the assumption of part rigidity. these methods could not be carried out on compliant assemblies and may lead to over or underestimation of assembly specifications. since compliant parts deform under assembly loads, there are additional variations in components incorporated in manufacturing tolerances. Therefore, Compliant STA methode have been developed to improve rigid body STA using finite element analisis (FEA). A significant application of compliant STA is in the case of sheet metal assemblies which are widely used in aerospace industries, such as fuselage, rudder, wing flap, spoiler, ect. In assembling a sheet ,metal atructure, inevitably, there will be some residual stresses in the process. These stresses are arisen as a result of dealing with uncertein manufacturing dimensions. In this regard, assembly foeces, residuale stresses and corresponding deformations are considered as the assembly variables of interest in the compliant STA of sheet metal assemblise. The objective of such STA procedure is to predict hew sensitive deformations. stresses and assembly forces are to manufacturing tolerances. It can be accomplished by accounting for the statistical multivariate distribution of those variables in terms of manufacturing tolerances. It should be noted thet the variations of deformations and stresses among the various nodes are correlated rather than independent. This correlation, in fact, is occurred in consequence of interdependency between mating nodes thoughout the assembly. finally, the acceptance fraction, a common measure for estimating the overall assembly quality, can also be calculated by integrating the multivariate distribution of the assembly variables of interest, Thus, STA procedure can predict cost effectiveness of an assembly when parts are designed and before being manufactured.