Monitoring multivariate simple linear profiles using individual observations

Abstract

In quality control applications, the quality of a product may effectively be characterized by a relationship between one or more variables that is typically referred to as a profile. In this paper, we propose two control charts, namely the maximum multivariate EWMA (MEWMA) and maximum double MEWMA charts for monitoring the parameters of a multivariate simple linear profile using the individual observations. Moreover, the sensitivities of these control charts are also enhanced with the variable sampling interval feature. The Monte Carlo simulation method is used to compute the zero-state and steady-state run-length characteristics of the proposed charts. Based on detailed run-length comparisons, it is found that the MaxDMEWMA chart is slightly more sensitive than the MaxMEWMA chart. A real dataset is also considered to support the theory.

Keywords:

• Average run length
• MaxMEWMA
• MaxDMEWMA
• Monte Carlo simulation
• profile monitoring
• statistical process control

2010 Mathematics Subject Classification:

• 62N10

Acknowledgments

The authors are thankful to the associate editor and the anonymous reviewer for providing useful comments that led to an improved version of the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).