- 期刊
A Mixed TCC Cumulative Sum-Double Moving Average Control Chart For Detecting Mean Shifts Under Symmetric And Asymmetric Distributions
摘要
Control charts are common methods for monitoring effectiveness. The mixed cumulative sum-double moving average (MCD) chart is a parametric control chart, and it is a helpful tool for detecting minute changes in the process mean. The Tukey control chart (TCC) is a nonparametric chart for a process without a distribution. This research aims to develop a new mixed control scheme, between the MCD chart and TCC, named Tukey cumulative sum-double moving average chart (MCD-TCC) to detect changes in process mean with symmetrical and asymmetrical distributions. The effectiveness of the MCD-TCC is evaluated using Monte Carlo (MC) simulation and compared to the cumulative sum (CUSUM), double moving average (DMA), MCD, mixed cumulative sum-Tukey (CUSUM-TCC), and mixed Tukey-double moving average (TCC-DMA) charts using average run length (ARL), and median run length (MRL) as the criteria for efficiency measurement. The study's findings for the process with asymmetrical distributions demonstrated that, for instances of minor shifts (δ < 0.25), the MCD-TCC performed better than the CUSUM, DMA, MCD, CUSUM-TCC, and TCC-DMA charts. In other shifts, TCC-DMA control charts perform better than other charts. Finally, a real data set is offered to demonstrate the application of the MCD-TCC.