白车身质量是汽车整车质量控制中的重要环节,针对白车身制造尺寸质量控制中检测数据属于小样本数据、数据处理分析不能采用一般大样本条件下统计分析方法的问题引入Bootstrap重采样Bayesi~方法.通过对白车身尺寸质量的不合格率进行定义,分析简单计算、滑动计算、β口分布Bayesian计算等3种估计不合格率的方法,引入Bootstrap重采样技术结合Bayesian方法进行不合格率的估计,并通过Madab软件对4种算法进行仿真比较.仿真结果表明,Bootstrap重采样Bayesian方法的预测精度高于其余3种方法,适用于小样本情况下白车身制造尺寸不合格率的估计.最后通过一个实例演示了Bootstrap重采样Bayesian方法在白车身制造尺寸不合格率估计中的应用流程.%The manufacturing accuracy of white auto body takes an important part in quality control of the whole auto manufacturing. In the white auto body manufacturing process, only small number of inspection samples can be obtained. Hence, quality control methods that require large number of samples are not ap-plicable. To solve this problem, Bayesian method combined with Bootstrap resampling technique is adopt-ed. After defining the failure rate of white body size, for comparison, simple calculation analysis, sliding calculation analysis, and Bayesian method based on β distribution are used to analyze the failure rate, re-spectively. Then, Bayesian method combined with Bootstrap resampling technique is applied to estimate the failure rate. Simulation based on Madab is used to compare the four methods. Result shows that Boot-strap resampling Bayesian method outperforms the others and it can be applied to estimate the failure rate with small number of samples. An example is given to show how the application of the proposed method.
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