Monitoring autocorrelated multivariate multiple linear profiles

Abstract

Abstract If the quality of a process can be represented by a functional relationship, a collection of this quality data is called a profile. In monitoring schemes, profile monitoring is used to evaluate the stability of a relationship. In some applications, quality data collected from continuous processes have time correlations and can thus be characterized by a linear relationship between more than one response and explanatory variables. Therefore, we investigate this type of multivariate multiple linear regression model with between‐profile correlations in this study. We propose two exponentially weighted moving average control charts for monitoring the regression parameters and the covariance matrix of the model. Our simulation results reveal that our proposed scheme has satisfactory performance in terms of the average run length and standard deviation run length criteria. Finally, we present an example using real data to demonstrate the applicability of the proposed scheme.

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