New Robust MEWMA Control Chart for Monitoring Contaminated Data
Faridzah Jamaluddin1, Hazlina Haji Ali, Sharipah Soaad Syed Yahaya3
1Faridzah Jamaluddin, School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Malaysia.
2Hazlina Haji Ali, School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Malaysia.
3Sharipah Soaad Syed Yahaya, School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Malaysia.
Manuscript received on 07 August 2019 | Revised Manuscript received on 14 August 2019 | Manuscript published on 30 August 2019 | PP: 2773-2780 | Volume-8 Issue-10, August 2019 | Retrieval Number: J95880881019/2019©BEIESP | DOI: 10.35940/ijitee.J9588.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Multivariate Exponential Weighted Moving Average (MEWMA), E2 control chart is a popular multivariate control chart for monitoring the stability of time series data (non-random pattern). However, in this paper, we have shown that the existing MEWMA, E2 control chart is sensitive in contaminated data or in the presence of outliers. To address this problem, this paper proposed an alternative MEWMA E2 control chart using robust mean vector and covariance matrix instead of the classical mean vector and covariance matrix respectively. The classical mean vector in MEWMA E2 control chart is replaced by Winsorized Modified One-step M-estimator (WM) while the classical covariance matrix is replaced by the Winsorized covariance matrix. The proposed MEWMA E2 control chart known as robust MEWMA control chart, denoted as RE2 control chart. The control limit for the RE2 control chart was calculated based on simulated data. The performance of RE2 and existing MEWMA E2 control charts are based on the false alarm rate. The result revealed that the RE2 control chart is more effective in controlling false alarm rates as compared to the existing MEWMA, E2 control chart. The zinc-lead flotation data show that the RE2 performs better in application.
Keywords: Control Chart, Contaminated Data, Multivariate Exponential Weighted Moving Average (MEWMA), Robust Estimator, Winsorized One-step M-Estimator (WM)
Scope of the Article: Health Monitoring and Life Prediction of Structures