Memory‐type multivariate charts with fixed and variable sampling intervals for process mean when covariance matrix is unknown

2019 ◽  
Vol 36 (1) ◽  
pp. 144-160
Author(s):  
Abdul Haq ◽  
Michael B. C. Khoo
Keyword(s):  
Covariance Matrix ◽  
Process Mean ◽  
Variable Sampling ◽  
Sampling Intervals ◽  
Memory Type

scholarly journals New One-Sided EWMA t Charts without and with Variable Sampling Intervals for Monitoring the Process Mean

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yan Wang ◽  
Xuelong Hu ◽  
Xiaojian Zhou ◽  
Yulong Qiao ◽  
Shu Wu
Keyword(s):  
Moving Average ◽  
Simulation Method ◽  
Sampling Interval ◽  
Vital Role ◽  
Process Mean ◽  
Statistical Process ◽  
Variable Sampling ◽  
Sampling Intervals ◽  
Process Variance ◽  
Weighted Moving Average

In statistical process control (SPC), t charts play a vital role in the monitoring of the process mean, especially when the process variance is unknown. In this paper, two separate upper-sided and lower-sided exponentially weighted moving average (EWMA) t charts are first proposed and the Monte Carlo simulation method is used to obtain their run length (RL) properties. Compared with the traditional one-sided EWMA t charts and several run rules t charts, the proposed charts are proven to have better performance than these competing charts. In addition, by adding the variable sampling interval (VSI) feature to the proposed charts, the new VSI one-sided EWMA t charts are shown to detect different shift sizes in the process more efficient than the chart without VSI feature. Finally, an example of a milk filling process illustrates the use of the charts.

An EWMA t chart with variable sampling intervals for monitoring the process mean

2012 ◽  
Vol 66 (1-4) ◽  
pp. 125-139 ◽  
Author(s):  
Reza Baradaran Kazemzadeh ◽  
Mahdi Karbasian ◽  
Mohammad Ali Babakhani
Keyword(s):  
Process Mean ◽  
Variable Sampling ◽  
Sampling Intervals
Sign in / Sign up

Export Citation Format

Share Document