International Journal of Industrial Engineering & Production Management

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In certain statistical process control applications, quality of a process or product can be characterized by a function between response variable and one or more independent variables. This function commonly referred to as profile. Response variable can be continuous or discrete. All of the research assumes that the response variable is continuous. Whereas, some of the potential applications of profile monitoring are cases where the output can be modeled using polytomous (especially multinomial) or binary logistic regression models. Polytomous response variables, especially multinomial variables, can have various applications especially in service industry. In this paper, we propose some methods for monitoring a profile when the process output is a multinomial response variable. Multinomial logistic regression (OLR) provides the basis for our profile model. Performances of the proposed methods in terms of the signal probability for different out-of-control scenarios is compared based on simulation studies.

Keywords: Statistical Control Process, Signal Probability, Logistic Regression, Profile, Control Chart, Hotelling, Likelihood ratio test

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