NDLI: Comparing the inertial effect of MEWMA and multivariate sliding window schemes with confidence control charts

Content Provider	Springer Nature Link
Author	Moraes, D. A. O. Oliveira, F. L. P. Duczmal, L. H. Cruz, F. R. B.
Copyright Year	2015
Abstract	In practical applications of multivariate sliding window (SW) control charts, a considerable amount of difficulty lies in selecting parameters related to the window size and to the disposal of past observations. Although widely used for pattern recognition problems, to the best of the authors’ knowledge, there have been no comparative analyses of the efficiencies of multivariate SW schemes and more traditional and easy-to-apply control charts, such as Hotelling’s T 2 and the multivariate exponentially weighted moving average (MEWMA) control charts. The present work applies a transformed statistic called confidence control chart (CCC), which standardizes all the control charts in the 0–01 interval to improve visualization, and comparisons are made in terms of the average run length (ARL). Therefore, the purpose of this paper is to present a simulation study to compare the inertial effect of estimating the actual mean vector through the SW and the MEWMA schemes. Three types of SW schemes were tested, including uniform, linear, and exponential weights. In addition to providing equivalences between the smoothing parameter of the MEWMA method and the window sizes for the bivariate case, the results show that multivariate SW schemes suffer from the inertial effect more than MEWMA charts. In this sense, the user is encouraged to apply both control charts to avoid detection delay.
Starting Page	1457
Ending Page	1470
Page Count	14
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	84
Issue Number	5-8
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2015-09-17
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Process control Mean vectors Sliding window Simulation Average run length Industrial and Production Engineering Production Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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