Generalized contribution plots in multivariate statistical process monitoring

By Johan A. Westerhuis, Stephen P. Gurden, Age K. Smilde. 2000

510 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5b313802a19b30936e9896f41bc8207dfdb88636

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. S. Qin
2. Carlos F. Alcala
3. Manabu Kano
4. Yoshiaki Nakagawa
5. Steven X. Ding
6. Bin Jiang
7. Hongtian Chen
8. Zhiqiang Ge

In Mechanical Engineering

1. S. Qin
2. Bin Jiang
3. Hongtian Chen
4. Jianbo Yu

In Statistics and Probability

1. S. Qin
2. Carlos F. Alcala
3. Manabu Kano
4. Yoshiaki Nakagawa
5. Qingchao Jiang
6. Xue-feng Yan
7. Steven X. Ding
8. Bin Jiang

Citations in the corpus

• Reconstruction-based contribution for process monitoring (2009, background): “Westerhuis et al. [2000], for example, discuss that a fault in one variable smears to contributions of other variables in traditional contribution plots.”
• Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry (2008, background): “In practice, however, only a few variables whose contributions are positive large are important (Westerhuis et al., 2000).”
• On unifying multiblock analysis with application to decentralized process monitoring (2001, unknown): “As a result, negative contributions arise [19,20].”