High-dimensional data refers to a dataset that contains many variables or features, typically with many more features p than observations n (i.e. n<p). With technological advancements in sensors, high-dimensional data are becoming increasingly common in process-monitoring applications. Therefore, this study presents a comprehensive overview of high-dimen-sional monitoring methods, in which 82 articles published from 2004 to 2023 were found to be relevant. The literature on high-dimensional monitoring can be divided into three approaches: control charts based on dimension reduction, variable selection, and high-dimensional techniques. Furthermore, the literature on each approach is divided in terms of control chart structures such as memory-less (Hotelling's T2), memory type (multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM)), and others. Real-life datasets from different fields, such as industry, medical science, chemical engineering, and image processing, which have frequently been used in high-dimensional monitoring, are also listed. It is noted that the literature on high-dimensional monitoring increased after 2016, and most studies were designed using high-dimensional techniques. Moreover, most studies proposed memory types and other structures for monitoring high-dimensional data. This review article offers a comprehensive summary of the current state-of-the-art high-dimensional monitoring research and identifies potential areas for future research.

Fuhad Ahmed

Tahir Mahmood

Muhammad Riaz

Nasir Abbas

Quality Technology & Quantitative Management

QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT 是一本国际权威期刊，出版关于质量、可靠性、排队服务系统、应用统计（包括方法学、数据分析、模拟）及其在商业和工业管理中的应用的原创作品。该杂志使用统计方法发表理论和应用研究文章或展示新结果，这些文章解决或有可能解决现实世界的管理问题。

Quality Technology and Quantitative Management is an internationally recognized journal that publishes original works on quality, reliability, queuing service systems, applied statistics (including methodology, data analysis, and simulation), and their applications in business and industrial management. The journal employs statistical methods to present theoretical and applied research articles or showcase new results that address or have the potential to solve real-world management issues.

《Quality Technology and Quantitative Management》是一本国际权威期刊，专注于质量、可靠性、排队服务系统、应用统计（包括方法学、数据分析和模拟）及其在商业和工业管理中的应用。该期刊发表原创研究，使用统计方法探讨理论和应用问题，旨在解决或有潜力解决现实世界中的管理挑战。

Category	Quartile
工程技术	2
工程技术, 统计学与概率论	1
工程技术, 运筹学与管理科学	2
工程技术, 工程工业	3

Comprehensive review of high-dimensional monitoring methods: trends, insights, and interconnections

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Category	Quartile
STATISTICS & PROBABILITY	1