Fast initial response (FIR) features are generally used to improve the sensitivity of memory-type control charts by shrinking time-varying control limits in the earlier stage of the monitoring regime. This paper incorporates FIR features to increase the sensitivity of the homogeneously weighted moving average (HWMA) monitoring schemes with and without measurement errors under constant as well as linearly increasing variance scenarios. The robustness and the performance of the HWMA monitoring schemes are investigated in terms of numerous run-length properties assuming that the underlying process parameters are known and unknown. It is found that the FIR features improves the performance of the HWMA monitoring scheme as compared to the standard no FIR feature HWMA scheme, and at the same time, it is observed that the simultaneous use of a recently proposed FIR feature and multiple measurements significantly reduces the negative effect of measurement errors. An illustrative example on the volume of milk in bottles is used to demonstrate a real-life application.

中文翻译：

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在测量误差影响下，在具有估计参数的均匀加权移动平均图上使用快速初始响应特征

快速初始响应 (FIR) 功能通常用于通过在监测制度的早期阶段缩小时变控制限制来提高记忆型控制图的灵敏度。本文结合 FIR 特征来提高均匀加权移动平均 (HWMA) 监测方案的灵敏度，在恒定和线性增加方差的情况下有和没有测量误差。假设基础工艺参数已知和未知，HWMA 监测方案的稳健性和性能根据众多运行长度特性进行研究。发现与标准的无 FIR 特征 HWMA 方案相比，FIR 特征提高了 HWMA 监测方案的性能，同时，据观察，同时使用最近提出的 FIR 特征和多次测量显着减少了测量误差的负面影响。使用瓶装牛奶体积的说明性示例来演示实际应用。