Adaptive CUSUM and EWMA charts with auxiliary information and variable sampling intervals for monitoring the process mean

2020 ◽  
Author(s):  
Abdul Haq ◽  
Shareen Akhtar ◽  
Michael Boon Chong Khoo
Keyword(s):  
Auxiliary Information ◽  
Process Mean ◽  
Variable Sampling ◽  
Sampling Intervals

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.

A combined variable sampling interval and double sampling control chart with auxiliary information for the process mean

2019 ◽  
Vol 42 (6) ◽  
pp. 1151-1165 ◽  
Author(s):  
Adamu A Umar ◽  
Michael BC Khoo ◽  
Sajal Saha ◽  
Abdul Haq
Keyword(s):  
Steady State ◽  
Control Charts ◽  
Auxiliary Information ◽  
Sampling Interval ◽  
Double Sampling ◽  
Process Mean ◽  
Small Shift ◽  
Average Time To Signal ◽  
Variable Sampling Interval ◽  
Variable Sampling

In recent years, the suitable use of auxiliary information technique in control charts has shown an improved run length performance compared to control charts that do not have this feature. This article proposes a combined variable sampling interval (VSI) and double sampling (DS) chart using the auxiliary information (AI) technique (called VSIDS-AI chart, hereafter). The plotting-statistic of the VSIDS-AI chart requires information from both the study and auxiliary variables to efficiently detect process mean shifts. The charting statistics, optimal design and performance assessment of the VSIDS-AI chart are discussed. The steady-state average time to signal (ssATS) and steady-state expected average time to signal (ssEATS) are considered as the performance measures. The ssATS and ssEATS results of the VSIDS-AI chart are compared with those of the DS AI, variable sample size and sampling interval AI, exponentially weighted moving average AI (EWMA-AI) and run sum AI (RS-AI) charts. The results of comparison show that the VSIDS-AI chart outperforms the charts under comparison for all shift sizes, except the EWMA-AI and RS-AI charts for small shift sizes. An illustrative example is provided to demonstrate the implementation of the VSIDS-AI chart.

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
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