Statistical Process Monitoring is a statistical inference methodology that distinguishes itself by enabling the continuous assessment of system states through probabilistic modeling and anomaly detection techniques to identify deviations from expected operational behavior in predictive maintenance contexts.
728
Publications
38.6K
Citations
1.4K
Authors
586
Institutions
Publications per year
2017–2026
234
Publications
728
Statistical process monitoring: basics and beyond
S. Joe Qin · Journal of Chemometrics · 2003 · 1.6K citations
Engineering, Industrial Engineering, Systems Engineering +16
1–5 of 728
Authors
1.4K
- FTFugee Tsung
Hong Kong University of Science and Technology, Hong Kong SAR China
20 publications · 1.3K citations
18
h-index
- BH
13
h-index
- CT
13
h-index
- SJ
13
h-index
- WH
13
h-index
1–5 of 1.4K
Institutions
586
Hong Kong University of Science and Technology
Hong Kong, Hong Kong
21 h-index
39 publications
2K citations
Arizona State University
Tempe, United States
17 h-index
33 publications
2.6K citations
Tsinghua University
Beijing, China
17 h-index
55 publications
5.2K citations
Zhejiang University of Technology
Hangzhou, China
17 h-index
43 publications
2.8K citations
East China University of Science and Technology
Shanghai, China
17 h-index
54 publications
2.7K citations
Virginia Tech
Blacksburg, United States
17 h-index
33 publications
3.1K citations
Zhejiang University
Hangzhou, China
16 h-index
38 publications
1.7K citations
National University of Singapore
Singapore, Singapore
16 h-index
31 publications
1.2K citations
1–8 of 586
Venues
- Industrial & Engineering Chemistry Research
55 publications · 3.3K citations
32
h-index
- Quality and Reliability Engineering International
70 publications · 2.1K citations
25
h-index
- Journal of Quality Technology
34 publications · 3.5K citations
23
h-index
- Journal of Process Control
24 publications · 1.9K citations
22
h-index
- International Journal of Production Research
25 publications · 1.1K citations
21
h-index
1–5