An automotive body is composed of compliant sheet metal parts.Fast and exactly diagnosing variation sources is very important when assembly variations happen.This paper proposes a diagnosis method of multi fixture var...An automotive body is composed of compliant sheet metal parts.Fast and exactly diagnosing variation sources is very important when assembly variations happen.This paper proposes a diagnosis method of multi fixture variations based on the variation model of compliant sheet metal assembly.The assembly variation model is obtained by using the method of influence coefficients(MIC) and considering the manufacturing variations of compliant parts and multi fixture variations.The measurement point variations induced by part manufacturing variations are firstly removed from the measurement data.The variation patterns of multi fixture variations are constructed by column vectors of fixture variation sensitivity matrix.This method is proved to be feasible for exactly diagnosing the fixture variations and has higher diagnosis efficiency than designated component analysis(DCA).展开更多
Based on the manufacturing history chain, a component's macro residual stress is introduced to the subsequent assembly model. In the simulated method, the simulation cost is saved via mapping the bulk stress profi...Based on the manufacturing history chain, a component's macro residual stress is introduced to the subsequent assembly model. In the simulated method, the simulation cost is saved via mapping the bulk stress profile directly to the component compared to our previous study. It thus facilitates the finite element analysis(FEA) which takes the component location in blank and the thickness of blank as two influence parameters. The methodology is proved to be feasible by the validation experiment designed for a typical assembly structure from the aerospace industry. The results show that the bulk stress originating from material preparation affects the downstream large-scale assembly deformation. The investigation of this research helps systematically to improve compliant assembly precision.展开更多
基金the National Natural Science Foundation of China (No. 50705056)the National High Technology Research and Development Program (863) of China (No.2006AA04Z148)
文摘An automotive body is composed of compliant sheet metal parts.Fast and exactly diagnosing variation sources is very important when assembly variations happen.This paper proposes a diagnosis method of multi fixture variations based on the variation model of compliant sheet metal assembly.The assembly variation model is obtained by using the method of influence coefficients(MIC) and considering the manufacturing variations of compliant parts and multi fixture variations.The measurement point variations induced by part manufacturing variations are firstly removed from the measurement data.The variation patterns of multi fixture variations are constructed by column vectors of fixture variation sensitivity matrix.This method is proved to be feasible for exactly diagnosing the fixture variations and has higher diagnosis efficiency than designated component analysis(DCA).
基金the National Basic Research Program(973)of China(No.2010CB731703)the National Natural Science Foundation of China(No.51275308)
文摘Based on the manufacturing history chain, a component's macro residual stress is introduced to the subsequent assembly model. In the simulated method, the simulation cost is saved via mapping the bulk stress profile directly to the component compared to our previous study. It thus facilitates the finite element analysis(FEA) which takes the component location in blank and the thickness of blank as two influence parameters. The methodology is proved to be feasible by the validation experiment designed for a typical assembly structure from the aerospace industry. The results show that the bulk stress originating from material preparation affects the downstream large-scale assembly deformation. The investigation of this research helps systematically to improve compliant assembly precision.
