面向AMT的统计过程质量控制*(2)
作者:佚名; 更新时间:2014-12-05
式(7)生成标准正态分布的样本。变换标准正态分布的总体生成80组不同作用趋势的数据,其中20组数据为普通的,60组为三种复杂趋势,分别是小波动的持续上升、小波动的持续下降和循环趋势。
(7)
利用这80组数据,对所建立的神经网络进行训练取得了良好的效果。在对不同加工过程中所得到的20组实际数据的测试中,全部正确。对各种其它方法不易判断的复杂趋势具有良好的判断能力。
四、结论 本文在研究SPQC技术应用于先进制造环境下所存在的问题的基础上,提出了解决AMT生产环境下质量数据不足的问题的方法,给出了基于等效工序能力的统计过程控制图的控制变量的计算方法;分析表明这种质量控制方法能够有效地控制先进制造生产环境下生产过程的稳定,算法易于编程计算机化,是一种适用于AMT环境的统计过程质量控制技术。同时,利用以前馈型的反向传播神经网络算法为基础的模式识别技术,开发了加工过程异常模式的自动识别软件,应用表明具有良好的效果。
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Stasitical Process Quality Control Based on AMT Xu Chong,
Abstract:In this paper, the development of Statistical Process Quality Control in AMT is analyzed and the existent problem of applicated SPQC in AMT is discussed. Then according to the problem, the SPQC for low volume production module is proposed. The error pattern automatic distinction technology is also presented by using BP model neural network. keyword: AMT, SPQC, Patterns Distinction, Quality Assurance
Abstract:In this paper, the development of Statistical Process Quality Control in AMT is analyzed and the existent problem of applicated SPQC in AMT is discussed. Then according to the problem, the SPQC for low volume production module is proposed. The error pattern automatic distinction technology is also presented by using BP model neural network. keyword: AMT, SPQC, Patterns Distinction, Quality Assurance
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