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Adaptive multivariate statistical controlof the technological process


E.A. Zentsova – Post-graduate Student, Department «Applied Mathematics and Informatics», Ulyanovsk State Technical University
V.N. Klyachkin – Dr. Sc. (Eng.), Professor, Department «Applied Mathematics and Informatics», Ulyanovsk State Technical University

A multivariate process control is based on a sequential detection of changes in an independent random sequence. The distribution of time interval between two consecutive changes is commonly unknown. An analytical decision-making tool that indicates whether a corrective action should be carried out is a control chart. Adaptive charts might be considered if the aim is to detect process changes quickly and to correct them before specification limits are exceeded. Adjusted average time to signal measure, calculated through Markov chain approach, is applied to evaluate charts’ performance. Adaptive control charts with high frequency of switching between two sampling plans is difficult to implement. For the successful implementation of these charts the adjusted average time to signal needs to be minimized with constraints on the frequency of switches between sampling plans. In the present study this principle is applied for Hotelling's T2 control chart with variable sample size and sampling intervals.

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