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Survey on the theoretical research and engineering applications of multivariate statistics process monitoring algorithms: 2008–2017
Author(s) -
Wang Youqing,
Si Yabin,
Huang Biao,
Lou Zhijiang
Publication year - 2018
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.23249
Subject(s) - viewpoints , multivariate statistics , statistics , computer science , process (computing) , china , operations research , management science , mathematics , engineering , geography , art , archaeology , visual arts , operating system
Multivariate statistical process monitoring (MSPM) methods are significant for improving production efficiency and enhancing safety. However, to the authors’ best knowledge, there is no survey paper providing statistics of published papers over the past decade. In this paper, several issues related to MSPM methods are reviewed and studied. First, the annual publication numbers of journal articles concerning MSPM are provided to show the active development of this important research field and to point out several promising directions in the future. Second, the annual numbers of patents are also shown to demonstrate the practicality of different MSPM methods. Particularly, this paper also lists and analyzes the number of MSPM‐related publications in China. The statistics indicate that Chinese researchers and engineers may have different viewpoints from those of other countries, which results in different development trends of MSPM in China.