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首页> 外文期刊>Quality and Reliability Engineering International >DEVELOPING IDENTIFICATION TECHNIQUES WITH THE INTEGRATED USE OF SPC/EPC AND NEURAL NETWORKS
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DEVELOPING IDENTIFICATION TECHNIQUES WITH THE INTEGRATED USE OF SPC/EPC AND NEURAL NETWORKS

机译:通过结合使用SPC / EPC和神经网络来开发识别技术

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摘要

Recently,a great deal of research has focused on integrating statistical process(SPC)and engineering process control(EEC).Most of these studies have concluded that the integrated use of both SPC and EPC is superior in performance to the use of either alone .However, the majority of these studies have assumed that the assignable causes of a disturbance can be identified and removed as soon as the out -of -control signal is triggered by SPC. In practice, the identification of the assignable causes of a disturbance is not so straightforward. Using SPC and EPC control schemes, this study introduces a simple graphical aid technique to display the pattern of the underlying disturbance .Using EPC and neural network(NN)scheme, this study focuses on the development of another technique to identify the nature of the assignable causes of he underlying disturbance .The effectiveness and the superiority of the proposed approaches are demonstrated through a series of simulations.
机译:近年来,大量的研究集中在统计过程(SPC)和工程过程控制(EEC)的集成上。大多数研究得出的结论是,SPC和EPC的综合使用在性能上要优于单独使用两者。但是,这些研究中的大多数都假定,一旦SPC触发失控信号,就可以识别并消除引起干扰的原因。在实践中,确定干扰的可分配原因并不是那么简单。本研究使用SPC和EPC控制方案,引入了一种简单的图形辅助技术来显示潜在干扰的模式。使用EPC和神经网络(NN)方案,本研究着重于开发另一种技术来识别可分配物的性质潜在的干扰原因。通过一系列仿真证明了所提出方法的有效性和优越性。

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