基于多元混合模型的自相关多元线性剖面在线监测

IF 2.3 2区工程技术 Q3 ENGINEERING, INDUSTRIAL

Quality Technology and Quantitative Management Pub Date : 2022-01-03 DOI:10.1080/16843703.2021.2015834

Somayeh Khalili, R. Noorossana

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引用次数: 5

摘要

在过去的几年里，多变量多剖面监测得到了广泛的研究。这些研究大多假设观测结果是不相关的，这在实践中可能会被违背。本文提出了多元线性混合模型，使多元多元线性剖面的观测值之间具有相关性。为了监测第二阶段的随机效应和过程变异性，建议采用三种控制图。与现有方法的性能比较表明了所提控制图的优越性。最后，通过实例说明了所提方法的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Online monitoring of autocorrelated multivariate linear profiles via multivariate mixed models

ABSTRACT Multivariate multiple profile monitoring has been studied extensively over the past few years. Most of these studies assumed that the observations are uncorrelated, which could be violated in practice. In this paper, multivariate linear mixed model is proposed to allow correlation among observations of the multivariate multiple linear profiles. In order to monitor random effects and process variability in phase II, three control charts are suggested. The results of performance comparisons with an existing method show the superiority of the proposed control chart. Finally, the applicability of the proposed method is illustrated using a real case.

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来源期刊

Quality Technology and Quantitative Management ENGINEERING, INDUSTRIAL-OPERATIONS RESEARCH & MANAGEMENT SCIENCE

CiteScore

5.10

自引率

21.40%

发文量

审稿时长

>12 weeks

期刊介绍： Quality Technology and Quantitative Management is an international refereed journal publishing original work in quality, reliability, queuing service systems, applied statistics (including methodology, data analysis, simulation), and their applications in business and industrial management. The journal publishes both theoretical and applied research articles using statistical methods or presenting new results, which solve or have the potential to solve real-world management problems.