多元统计
二元分析
马尔可夫链
图表
多元分析
计算机科学
多元正态分布
信号(编程语言)
统计
控制图
自适应控制
数据挖掘
数学
控制(管理)
人工智能
操作系统
过程(计算)
程序设计语言
作者
Hamed Sabahno,Amirhossein Amiri,Philippe Castagliola
标识
DOI:10.1016/j.cie.2020.106524
摘要
This paper considers adaptive schemes for the simultaneous monitoring of the mean and variability of a multivariate normal quality characteristic. At first, we extend an already existing bivariate non-adaptive simultaneous control chart to a multivariate one. Then, we develop several adaptive schemes, which will cover both previously bivariate and newly multivariate charts. After having designed adaptive schemes for the multivariate chart, eight performance measures are computed based on the run length, time to signal, number of observations to signal and number of switches to signal and evaluated using a new Markov chain model. With the developed performance measures, non-adaptive and adaptive schemes under different mean, variability, simultaneous shift sizes, and different number of quality characteristics are compared. Our scheme is also compared to one of the best methods available in the literature. A numerical example is also provided in order to demonstrate how the adaptive scheme can be implemented in practice.
科研通智能强力驱动
Strongly Powered by AbleSci AI