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EFFECTIVE APPLICATION OF Q(R) CHARTS IN LOW-VOLUME MANUFACTURING

机译:Q(R)图在小批量制造中的有效应用

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Q charts provide means for statistical process control in low-volume processes and start-up phases of production. Concerns on their performance have led to research into different types of enhancements and much discussion on the appropriateness of these. Driven by the aim to implement control charts in the low-volume production of advanced wafer steppers, we investigate the performance of additional run rules and tightening control limits on the traditional Q chart compared with an exponentially weighted moving average (EWMA). Furthermore, we develop an alternative QR chart based on the mean moving range as estimator of the process standard deviation and consider the economics of low volume processes by means of a specific cost model .The comparisons are based on the run length distributions after a permanent shift and trend, both with an onset early in the process. Real life examples are given for various important variables in wafer stepper production, It is concluded that the EWMA based on QR statistics provides the best performance throughout, Competing alternatives with almost equal performance are the EWMA of Q statistics and the combination of four tests of special causes(1-of -1,2-of-3.4-of-5 and 8-of-8)applied on either the Q or QR chart. Overall ,the mean moving range performs better.
机译:Q图为小批量过程和生产的启动阶段中的统计过程控制提供了手段。对它们性能的关注导致对不同类型的增强功能进行了研究,并对它们的适用性进行了很多讨论。为了在高级晶圆步进器的小批量生产中实现控制图的目标驱动,我们与指数加权移动平均值(EWMA)相比,研究了传统Q图上附加运行规则和严格控制限制的性能。此外,我们基于平均移动范围作为过程标准偏差的估计值来开发替代QR图,并通过特定的成本模型来考虑小批量过程的经济性。比较基于永久转移后的行程长度分布和趋势,都在该过程的早期出现。给出了现实生活中晶片步进生产中各种重要变量的示例,得出的结论是,基于QR统计量的EWMA始终提供最佳性能,具有几乎相同性能的竞争替代品是Q统计量的EWMA和四种特殊测试的组合原因(在Q或QR图上应用(在1,1,2- of-3.4-of-5和8-of-8中)。总体而言,平均移动范围表现更好。

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