Identifying the Out-of-Control Variables of Multivariate Control Chart Using Ensemble SVM Classifiers_

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題名：	Identifying the Out-of-Control Variables of Multivariate Control Chart Using Ensemble SVM Classifiers
書刊名：	工業工程學刊
作者：	鄭春生／李虹葶
作者(外文)：	Cheng, Chuen-sheng／Lee, Hung-ting
出版日期：	2012
卷期：	29:5
頁次：	頁314-323
主題關鍵詞：	多變量管制圖；異常來源辨識；整體式；支援向量機；multivariate control chart；interpretation of signal；ensemble classifiers；support vector machine
原始連結：	連回原系統網址
相關次數：	被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0) 排除自我引用:0 共同引用:0 點閱:31

Out-of-control signals in multivariate charts may be caused by one or few variables or a set of variables. Multivariate process control often encounters with the diagnosis or interpretation difficulty of an out-of-control signal to determine which variable is responsible for the signal. In this article, we formulate the diagnosis of out-of-control signal as a classification problem. The proposed system includes a shift detector and a classifier. The traditional multivariate chart works as a mean shift detector. Once an out-of-control signal is generated, an SVM-based ensemble classifier is used to recognize the variables that have shifted. We propose using subgroup data and extracted features (sample mean and Mahalanobis distance) as the input vectors of classifier. The performance of the proposed system was evaluated by computing its classification accuracy. We use the traditional decomposition method as a benchmark for comparison. The simulation studies indicate that the proposed ensemble classification model is a successful method in identifying the source of the mean change. The results also reveal that SVM using extracted features as input vector has slightly better classification performance than using raw data as input. The proposed method may facilitate the diagnosis of the out-of-control signal.

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期刊論文
1.	Hsu, C.-W.、Lin, C.-J.(2002)。A comparison of methods for multiclass support vector machines。IEEE Transactions on Neural Networks，13(2)，415-425。
2.	Wang, T.Y.、L.H. Chen(2002)。Mean shifts detection and classification in multivariate process: A neuralfuzzy approach。Journal of Intelligent Manufacturing，13，211-221。
3.	Yu, J.B.、L.F. Xi(2009)。A neural network ensemblebased model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes。Expert Systems with Applications，36，909-921。
4.	Yu, J. B.、Xi, L. F.(2009)。A hybrid learning-based model for on-line monitoring and diagnosis of outof- control signals in multivariate manufacturing processes。International Journal of Production Research，47(15)，4077-4108。
5.	Yu, J. B.、Xi, L. F.、Zhou, X. J.(2009)。Identifying source(s) of out-of-control signals in multivariate manufacturing processes using selective neural network ensemble。Engineering Applications of Artificial Intelligence，22(1)，141-152。
6.	Niaki, S.T.A.、B. Abbasi(2005)。Fault diagnosis in multivariate control charts using artificial neural networks。International Quality and Reliability Engineering，21(8)，825-840。
7.	Shao, Y.E.、C.H. Wu、B.Y. Ho、B.S. Hsu(2008)。A neural network-based approach to identifying outof- control variables for multivariate control charts。Lecture Notes in Computer Science，5236，644-652。
8.	Kotsiantis, S. B.、Pintelas, P. E.(2004)。Combining bagging and boosting。International Journal of Computational Intelligence，1(4)，324-333。
9.	Mason, R. L.、Tracy, N. D.、Young, J. C.(1995)。Decomposition of T2 for multivariate control chart interpretation。Journal of Quality Technology，27(2)，99-108。
10.	Murphy, B. J.(1987)。Selecting out-of-control variables with T2 multivariate quality procedures。The Statistician，36(5)，571-583。
11.	Hansen, L.、P. Salamon(1990)。Neural network ensembles。IEEE Transactions on Pattern Analysis and Machine Intelligence，12，993-1001。
12.	Hwarng, H.B.(2009)。Toward identifying the source of mean shift in multivariate SPC: a neural network approach。International Journal of Production Research，46(20)，5531-5559。
13.	Kim, M. J.、Kang, D. K.(2010)。Ensemble with neural networks for bankruptcy prediction。Expert Systems with Applications，37(4)，3373-3379。
14.	Das, N.、V. Prakash(2008)。Interpreting the out-ofcontrol signal in multivariate control chart – a comparative study。International Journal of Advanced Manufacturing Technology，37，966-979。
15.	Dietterich, T. G.(1997)。Machine learning research: Four current directions。AI Magazine，18(4)，97-136。
16.	Alfaro, E.、J.L. Alfaro、M. Ga' mez、García, N.(2009)。A boosting approach for understanding out-of-control signals in multivariate control charts。International Journal of Production Research，47，6821-6831。
17.	Aparisi, F.、Avendaño, G.、Sanz, J.(2006)。Techniques to interpret T2 control chart signals。IIE Transactions，38(8)，647-657。
18.	Chen, L. H.、Wang, T. Y.(2004)。Artificial neural networks to classify mean shifts from multivariate X2 chart signals。Computers and Industrial Engineering，47(2/3)，195-205。
19.	Cheng, C. S.、Cheng, H. P.(2008)。Identifying the Source of Variance Shifts in the Multivariate Process Using Neural Network and Support Vector Machines。Expert Systems with Applications，35(1/2)，198-206。
20.	Guh, R. S.(2007)。On-line identification and quantification of mean shifts in bivariate processes using a neural network-based approach。Quality and Reliability Engineering International，23(3)，367-385。
21.	Sun, R.、Tsung, F.(2003)。A kernel-distance-based multivariate control chart using support vector Methods。International Journal of Production Research，41(13)，2975-2989。
22.	Chang, C.-C.、Lin, C.-J.(2011)。LIBSVM: A library for support vector machines。ACM Transactions on Intelligent Systems and Technology，2(3)，27-21。
23.	Yu, L.、Yue, W.、Wang, S.、Lai, K. K.(2010)。Support vector machine based multiagent ensemble learning for credit risk evaluation。Expert Systems with Applications，37(2)，1351-1360。
24.	Burges, C. J. C.(1998)。A Tutorial on Support Vector Machines for Pattern Recognition。Data Mining and Knowledge Discovery，2(2)，121-167。
25.	Mason, R. L.、Young, C. J.(1999)。Improving the Sensitivity of the T? Statistic in Multivariate Process Control。Journal of Quality Technology，31(2)，155-165。
26.	Runger, G. C.、Alt, F. B.、Montgomery, D. C.(1996)。Contributors to a Multivariate Statistical Process Control Signal。Communications in Statistics-Theory and Methods，25(10)，2203-2213。

會議論文
1.	Cheng, C.S.、H.P. Cheng、K.K. Huang(2009)。Interpreting the mean shift signals in multivariate control charts using support vector machine-based classifier。IEEE International Conference on Industrial Engineering and Engineering Management，(會議日期: 20091208-1211)。Hong Kong China。429-433。
2.	Aparisi, F、Avendaño, G、Sanz, J.(2007)。Neural networks to identify the out-of-control process variables when a MEWMA chart is employed。The 16th IASTED International Conference on Applied Simulation and Modelling，(會議日期: 20070829-0831)。Palma De Mallorca。230-235。

圖書
1.	Montgomery, D. C.(2009)。Statistical Quality Control。New York：John Wiley & Sons。
2.	Vapnik, V. N.(2000)。The Nature of Statistical Learning Theory。New York：Springer。

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