Hybrid EWMA Control Chart under Bayesian Approach Using Ranked Set Sampling Schemes with Applications to Hard-Bake Process

A memory-type control chart is an important tool of statistical process for monitoring small to moderate shifts in the manufacturing process. Using prior information by Bayesian approach helpful charts. In this paper, a new hybrid exponentially weighted moving average (HEWMA) suggested under theory using ranked set sampling (RSS) schemes posterior and predictive distribution with informative different loss functions (LFs). The extensive Monto Carlo simulation conducted evaluate overall performance proposed HEWMA through average-run-length (ARL) standard-deviation run-length (SDRL). Finally, numerical example hard-bake semiconductor used check working execution control-chart RSS schemes. results reveal that more sensitive detecting out-of-control signals than AEWMA control-charts simple random sampling.