An EWMA -based method for monitoring polytomous logistic profiles

Abstract

In certain statistical process control applications, quality of a process or product can be characterized by a function commonly referred to as profile. Some of the potential applications of profile monitoring are cases where the quality characteristic can be modeled using dichotomous or polytomous variables. Polytomous variables, especially ordinal variables, have various applications. An ordinal (or ordered) variable is a categorical variable whose values are related in a greater/lesser sense. In this paper, we proposed three methods for monitoring a profile when the process/service output is an ordinal response variable. Ordinal logistic regression (OLR) provides the basis for our profile model. Three methods including chi-square statistics, exponentially weighted moving average (EWMA) statistics, and combination of these two statisticsare proposed to monitor OLR profiles in phase II. The performances of these three methodsare evaluated by average run length criterion (ARL).

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