Change point estimation in multi-attribute processes

Identification of the change point in multi-attribute processes make the corrective measures to be employed sooner. This of course results in considerable amount of time and money savings. In real-world problems, since most of the process changes are due to instantaneous causes (step-change), a new method is proposed in this paper to derive the maximum likelihood estimator of the time of a step-change in the mean vector of multi-attribute processes. The results of a performance study based on a numerical example are encouraging.