Mean shifts detection and classification in multivariate process: A neural-fuzzy approach

Journal of Intelligent Manufacturing

Volumn 13, Issue 3, 2002, Pages 211-221

  Wang, Tai Yue ^a   Chen, Long Hui ^a  

^a NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Control charts; Fuzzy set theory; Multivariate process; Neural networks; Statistical process control

Indexed keywords

BACKPROPAGATION; COMPUTER SIMULATION; DECISION THEORY; FUZZY SETS; MEMBERSHIP FUNCTIONS; NEURAL NETWORKS; QUALITY CONTROL; STATISTICAL METHODS;

CONTROL CHARTS; MULTIVARIATE PROCESS; NEURAL-FUZZY APPROACH;

STATISTICAL PROCESS CONTROL;

EID: 0036610685     PISSN: 09565515     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1015738906895     Document Type: Article

References (20)

1. A neural fuzzy control chart for detecting and classifying process shifts
2. A two-stage network approach for process variance change detection and classification
3. A multi-layer neural network model for detecting changes in the process mean
4. Multivariate generalizations of cumulative sum quality control schemes
5. Identification of change structure in statistical process control
6. Back-propagation algorithm which varies the number of hidden units
7. An integrated neural network approach for simultaneous monitoring of process mean and variance shifts-a comparative study
8. Multivariance quality control-illustrated by the air testing of sample bombsights
9. X-bar control chart pattern identification through efficient off-line neural network training
10. Multivariate quality control
11. A multivariate exponentially weighted moving average control chart
12. A review of multivariate control charts
13. 2 for multivariate control chart interpretation
14. Monitoring a multivariate step process
15. 2 control chart signals
16. A comparison of neural networks to SPC charts
17. Multivariate quality control using finite intersection tests
18. A review of neural networks for statistical process control