Paper Title:
NDA Based Hierarchical Classification Scheme for Identifying the Contributors to a Multivariate Control Chart
  Abstract

Many multivariate control charts have been proposed for monitoring several related quality characteristics simultaneously. However, even when an out-of-control signal is detected, the employed multivariate control charts generally do not provide any interpretable information associated with that signal. That is, the contributors of the out-of-control event can not be identified by the charts. Hence, how to tackle this interpretation problem effectively is an important issue in multivariate process control. One rarely addressed but very crucial property of this interpretation problem is that the number of possible outcomes can be very large. According to this key property, a nonparametric discriminant analysis (NDA)-based hierarchical classification scheme is proposed in this paper. A simulation experiment including several popular classification methods was conducted for evaluating the performance of the proposed method. The result shows that our proposed scheme is very competitive when measured against these popular methods.

  Info
Periodical
Key Engineering Materials (Volumes 467-469)
Edited by
Dehuai Zeng
Pages
427-432
DOI
10.4028/www.scientific.net/KEM.467-469.427
Citation
H.Y. Huang, J. C. Chien, "NDA Based Hierarchical Classification Scheme for Identifying the Contributors to a Multivariate Control Chart", Key Engineering Materials, Vols. 467-469, pp. 427-432, 2011
Online since
February 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Jian Zhang, Li Ling Bo, Jia Wei Xu, Seop Hyeong Park
Abstract:PCA plus SVM is a popular framework for classification problems. On the one hand, it can avoid the SVM kernel Gram to become overlarge and...
1031
Authors: Shi Ping Li, Yu Cheng, Hui Bin Liu, Lin Mu
Chapter 1: Mechanic Manufacturing System and Automation
Abstract:Linear Discriminant Analysis (LDA) [1] is a well-known method for face recognition in feature extraction and dimension reduction....
58
Authors: Ke Guo, Yi Zhu, Ye San
Chapter 1: Mechatronics
Abstract:Fault diagnosis of analog circuits is essential for guaranteeing the reliability and maintainability of electronic systems. Analog circuit...
1130
Authors: De Han Luo, Ya Wen Shao
Chapter 10: Intelligence Algorithm, Optimization Algorithm and their Applications
Abstract:Linear discriminant analysis (LDA) is a popular method among pattern recognition algorithms of machine olfaction. However, “Small Sample...
1532
Authors: Xiao Hong Wu, Wen Jie Xu, Bin Wu, Sheng Wei Qiu
Chapter 5: Control, Measurement and Monitoring: Technologies and Solutions
Abstract:Principal component analysis (PCA) and kernel Fisher discriminant analysis (KFDA) were applied to grade Fuji apples combined with near...
529