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Optimization of multivariate statistical process control

Keywords:

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


Quality assurance in radio electronics equipment manufacturing is largely connected with the stability assurance of the corresponding process. Ways to assess stability of statistically independent and related quality characteristics while investigating multivariate process are different. The most widely used tools for the former are Shewhart control charts for mean and range or standard deviation and Hotelling multivariate control charts - for the latter. Traditionally, control limits and sample size are determined according to statistical criteria, and the frequency of sampling is treated analytically depending on the process behavior. However, this approach doesn’t take into consideration such economic consequences as the costs of sampling and testing, the costs of repairing or correcting the process, the costs incurred by false alarms and the costs associated with producing nonconforming items. The main objective of this study is to determine the parameters of multivariate statistical process control in order to ensure that the criteria of effectiveness are fulfilled and optimized.
References:

 

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June 24, 2020
May 29, 2020

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