A Synthetic Control Chart for Monitoring Process Variability

2013 ◽  
Vol 30 (8) ◽  
pp. 1301-1309 ◽  
Author(s):  
S. V. Rajmanya ◽  
V. B. Ghute
Keyword(s):  
Control Chart ◽  
Synthetic Control ◽  
Process Variability ◽  
Monitoring Process

Multiobjective design of an S control chart for monitoring process variability

2012 ◽  
Vol 2 (4) ◽  
pp. 408 ◽  
Author(s):  
Abdul Sattar Safaei ◽  
Reza Baradaran Kazemzadeh ◽  
Seyed Taghi Akhavan Niaki
Keyword(s):  
Control Chart ◽  
Process Variability ◽  
Monitoring Process ◽  
Multiobjective Design

A multivariate EWMA control chart for monitoring process variability with individual observations

2005 ◽  
Vol 37 (11) ◽  
pp. 1023-1035 ◽  
Author(s):  
Arthur B. Yeh ◽  
Longcheen Huwang ◽  
Chien-Wei Wu
Keyword(s):  
Control Chart ◽  
Process Variability ◽  
Ewma Control Chart ◽  
Monitoring Process

A Comparative Analysis of Control Charts for Monitoring Process Mean

2021 ◽  
Vol 12 (3) ◽  
pp. 2616-2622
Author(s):  
You Huay Woon
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Moving Average ◽  
False Alarms ◽  
Synthetic Control ◽  
Implementation Cost ◽  
Shewhart Chart ◽  
Monitoring Process ◽  
Synthetic Chart ◽  
The Cost

Control charts serve as an effective tool for controlling and monitoring process quality in industries of production and service. The Shewhart chart is the first control chart that was used to detect large mean shifts in a process. Since then, to increase the Shewhart chart’s sensitivity, synthetic type control charts, such as synthetic control chart, side sensitive group runs (SSGR) control chart, have been proposed. SSGR chart ismore efficient compared to the Shewhart chart and synthetic chart,primarily due to the side sensitive feature in SSGR chart. Meanwhile, exponentially weighted moving average (EWMA) chart isoften used to detect small process changes. In practice, the evaluation of a control chart’s performance is vital. Nevertheless, the cost of implementing a control chart is an important factor that influences the choice of a control chart. The cost of repairs, sampling, nonconforming products from a failure in detecting out-of-control status, and investigating false alarms, can be significantly high. Therefore, the aim of this paper is to compare the implementation cost of synthetic, SSGR and EWMA charts, so that quality practitioners can identify the most cost-effective chart to implement. Here, the cost function was adopted to compute the implementation cost of the control chart. According to the findings, quality practitioners are recommended to adopt the SSGR chart,since it is more economical compared to the synthetic chart. However, the cost to implement anEWMA chart is higher than the synthetic and SSGR charts. In light of this, this study allows for quality practitioners to have a better idea on the selection of the control chart to implement, with respect to its cost.

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