Results of the Development of a Nonparametric Signed-Rank MEWMA Control Chart for Monitoring Location Process

• Activity Number: 354
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Quality and Productivity Section
• Author(s): Jamil Zeinab*+ and Jay Schaffer
• Companies: University of Northen Colorado and University of Northern Colorado
• Keywords: SRMEWMA ; MEWM Hotelling's T ; Affine-Invariant ; SPC ; Elliptically Symmetrical ; Skewed Distribution

Abstract

Multivariate SPC charts for detecting possible shifts in mean vectors assume that data observations vectors follow a multivariate normal distribution. Nonparametric SPC charts are increasingly becoming viable alternatives to parametric counterparts in detecting process shifts when underlying process output distribution is unknown. This study proposes a new nonparametric signed-rank multivariate EWMA-type (SRMEWMA) control chart for monitoring location parameters. The proposed control chart is based on adapting a multivariate spatial signed-rank test. The weighted version of this test is used to formulate the charting statistic by incorporating the exponentially weighted moving average (EWMA) scheme. The average run length (ARL) of the proposed scheme will be computed using Simulation for select combinations of soothing parameter, shift, and number of p-variate quality characteristics. The ARL performance will be compared to the performance of the multivariate exponentially moving average (MEWMA) and Hotelling T2 and the control charts for observation vectors sampled the multivariate normal, multivariate t, and multivariate gamma distributions.