A Variable Sampling Interval Multivariate Exponentially Weighted Moving Average Control Chart for Monitoring the Gumbel’s Bivariate Exponential Data

The general assumption for designing a multivariate control chart is that the multiple variables are independent and normally distributed. This may not be tenable in many practical situations, because with dependency often need to monitored simultaneously ensure process in-control. Gumbel’s Bivariate Exponential (GBE) distribution considered better model skewed data reliability analysis. In this paper, Multivariate Exponentially Weighted Moving Average (MEWMA) Variable Sampling Interval (VSI) feature developed monitor mean vector of GBE model. Monte-Carlo simulations used calculate ATS (Average Time Signal) values proposed VSI MEWMA three different types shifts. Meanwhile, some tables provided show performances designed parameters. Furthermore, both zero- steady-state compared those FSI (Fix Interval) chart. Comparative results superior its counterpart monitoring data. addition, numerical example performs well