Estimating σ and Improving Control Limits with RWAV for Normal and Non-normal Processes

ABSTRACT

In this article, we compare the statistical properties of , , and RWAV methods for estimation of variance of a process for quality control purposes. We investigate effects of non-normality for different estimators. Our results indicate that RWAV gives the best estimates of the standard deviations for both normal and non-normal processes. We recommend the construction of control charts with RWAV.

KEYWORDS:

• estimation
• mean and range charts
• process control
• quality control

ACKNOWLEDGEMENTS

The authors thank the editor and two anonymous referees for their assistance.

Notes

*WINNER means the estimator with smallest MAE among the three under certain process conditions. For example, if a cell is the WINNER and is column RWAV, it means RWAV possesses a smaller MAE than /c ₄ and /d ₂. MAE is the WINNER and is shown at the cell on the left.