Abstract
In this paper, gamma (λ, 2) distribution is considered as a failure model for the economic statistical design of x̄ control charts. The study shows that the statistical performance of control charts can be improved significantly, with only a slight increase in the cost, by adding constraints to the optimization problem. The use of an economic statistical design instead of an economic design results in control charts that may be less expensive to implement, that have lower false alarm rates, and that have a higher probability of detecting process shifts. Numerical examples are presented to support this proposition. The results of economic statistical design are compared with those of a pure economic design. The effects of adding constraints for statistical performance measures, such as Type I error rate and the power of the chart, are extensively investigated.
| Original language | English |
|---|---|
| Pages (from-to) | 397-409 |
| Number of pages | 13 |
| Journal | Journal of Applied Statistics |
| Volume | 30 |
| Issue number | 4 |
| DOIs | |
| State | Published - May 2003 |
Bibliographical note
Funding Information:Financial assistance from the Natural Science and Engineering Research Council (NSERC) of Canada for the support of this collaborative research is gratefully acknowledged. The authors also acknowledge the King Fahd University of Petroleum and Mineral for facilitating this project. The valuable suggestions of the referee are greatly appreciated.
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty