On improved dispersion control charts under ranked set schemes for normal and non-normal processes

In manufacturing industries, control charts are the promising statistical tools used for an efficient monitoring of processes. These charts enhance the product quality by timely signaling for special variations at any stage of the process. There are two common concerns in statistical process monitoring, location and variability of the quality characteristic of interest. Besides location parameter, the monitoring of process dispersion remained a matter of concern for researchers. The conventional simple random sampling (SRS) is a usual practice; however, ranked set sampling (RSS) schemes are very effective methods of choosing sample values. This study intends to design and investigate dispersion control charts under different RSS strategies for normal and non-normal processes. We have considered RSS, median ranked set sampling (MRSS), and extreme ranked set sampling (ERSS) schemes to design dispersion control charts. The performance of the existing and the proposed control charts is evaluated in terms of relative efficiency and power for normal and a variety of non-normal distributions. The comparative analysis revealed that the proposed structures outperform the existing charts. The application of the proposed procedures is also shown for a bottles filling process for an efficient and timely signaling of any special causes in the process.