A homogenously weighted moving average scheme for observations under the effect of serial dependence and measurement inaccuracy

IF 1.6 3区工程技术 Q4 ENGINEERING, INDUSTRIAL International Journal of Industrial Engineering Computations Pub Date : 2021-01-01 DOI:10.5267/J.IJIEC.2021.5.003

Maonatlala Thanwane, S. C. Shongwe, Muhammad Shahzad Aslam, J. Malela‐Majika, M. Albassam

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引用次数: 1

Abstract

The combined effect of serial dependency and measurement errors is known to negatively affect the statistical efficiency of any monitoring scheme. However, for the recently proposed homogenously weighted moving average (HWMA) scheme, the research that exists concerns independent and identically distributed observations and measurement errors only. Thus, in this paper, the HWMA scheme for monitoring the process mean under the effect of within-sample serial dependence with measurement errors is proposed for both constant and linearly increasing measurement system variance. Monte Carlo simulation is used to evaluate the run-length distribution of the proposed HWMA scheme. A mixed-s&m sampling strategy is incorporated to the HWMA scheme to reduce the negative effect of serial dependence and measurement errors and its performance is compared to the existing Shewhart scheme. An example is given to illustrate how to implement the proposed HWMA scheme for use in real-life applications.

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在序列依赖和测量不精度影响下的均匀加权移动平均方案

已知串行依赖性和测量误差的联合效应会对任何监测方案的统计效率产生负面影响。然而，对于最近提出的均匀加权移动平均(HWMA)方案，已有的研究仅关注独立且同分布的观测值和测量误差。因此，本文提出了在样本内序列依赖与测量误差的影响下，对测量系统方差恒定和线性增加的过程均值进行监测的HWMA方案。利用蒙特卡罗仿真对所提出的HWMA方案的行程分布进行了评估。为了减少序列依赖和测量误差的负面影响，在HWMA方案中引入了混合采样策略，并将其性能与现有的Shewhart方案进行了比较。给出了一个示例来说明如何实现所提出的HWMA方案，以便在实际应用中使用。

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