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
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).
