In order to assess the comprehensive quality of Jeep front-flank bracket rationally and effectively, use K means cluster method to analyze the cluster of condition attribute data, data separated into categories will be discretizated into integer according to the characteristics of the data distribution. In order to reduce the workload of detection and avoid the interference of complex data, use rough set toolbox to reduce attributes and get core data. In order to guarantee the result correct and avoid local optimal solution, the Genetic algorithm that can realize the parallel search is used to seek the optimal solution interval, the Simplex search optimization method is used to determine the optimal solution. In order to reflect the quality holographicly, use weibull distribution that has a wide applicability to calculate the similarity, that this process use the Adaptive integration method and Cubic spline interpolation to eliminate the accumulation error and guarantee the accuracy of calculation results. The method proposed in this paper can reduce the workload of measurement and calculation, save effectively time, improve the testing efficiency, in theory and practice, this paper realize the beneficial exploration around the comprehensive quality assessment of Jeep front-flank bracket.