Multivariate Statistical Process Monitoring
Multivariate Statistical Process Monitoring is a statistical methodology within process monitoring that simultaneously analyzes multiple interrelated process variables using multivariate statistical techniques to detect abnormal patterns or trends indicative of process drift or failure in the context of Continued Process Verification.
394
Publications
26.6K
Citations
871
Authors
356
Institutions
Publications per year
2017–2026
116
Variants
Mspm
394
1–5 of 394
871
11
h-index
11
h-index
9
h-index
9
h-index
8
h-index
1–5 of 871
356
East China University of Science and Technology
Shanghai, China
14 h-index
43 publications
2.5K citations
Tsinghua University
Beijing, China
12 h-index
25 publications
3.5K citations

McMaster University
Hamilton, Canada
10 h-index
22 publications
8.8K citations

Zhejiang University
Hangzhou, China
10 h-index
27 publications
1.1K citations

Beijing University of Chemical Technology
Beijing, China
10 h-index
30 publications
2.1K citations
Pohang University of Science and Technology
Pohang, South Korea
10 h-index
29 publications
2.9K citations

Northeastern University
Shenyang, China
10 h-index
23 publications
992 citations

Illinois Institute of Technology
Chicago, United States
9 h-index
19 publications
1.9K citations
1–8 of 356
31 publications · 2.4K citations
22
h-index
21 publications · 1.5K citations
21
h-index
20 publications · 5.5K citations
18
h-index
17 publications · 1.5K citations
17
h-index
18 publications · 1.5K citations
14
h-index
1–5