A likelihood control chart for monitoring bivariate lifetime processes

Abstract

In this survey, two new control charts CCLR and CCALR for bivariate exponential variables by dependence structure based on Farlie-Gumbel-Morgenstern copula model are introduced. Simulation study is done to make a comparison between two proposed control charts in terms of average run length (ARL). Results show that the CCALR performs better than CCLR. Anumerical example is provided to fortify the theoretical findings.

Keywords

• control chart
• bivariate exponential distribution
• farlie-gumbel-morgenstern copula
• likelihood ratio test
• average run length