International Journal of Industrial Engineering and Production Research (Jun 2013)

Monitoring Multinomial Logit Profiles via Log-Linear Models (Quality Engineering Conference Paper)

  • Rassoul Noorossana,
  • Abbas Saghaei,
  • Hamidreza Izadbakhsh,
  • Omid Aghababaei

Journal volume & issue
Vol. 24, no. 2
pp. 137 – 142

Abstract

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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 quality characteristic of interest is modelled using binary,multinomial or ordinal variables. In this paper, profiles with multinomial response are studied. For this purpose, multinomial logit regression (MLR) is considered as the basis.Then, the MLR is converted to Poisson GLM with log link. Two methods including Multivariate exponentially weighted moving average (MEWMA) statistics, and Likelihood ratio test (LRT) statistics are proposed to monitor MLR profiles in phase II. Performances of these three methods are evaluated by average run length criterion (ARL). A case study from alloy fasteners manufacturing process is used to illustrate the implementation of the proposed approach. Results indicate satisfactory performance for the proposed method.

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