New Dual Auxiliary Information-Based EWMA Control Chart with an Application in Physicochemical Parameters of Ground Water

2018 ◽  
Vol 43 (3) ◽  
pp. 1171-1190 ◽  
Author(s):  
Shahid Hussain ◽  
Lixin Song ◽  
Rashid Mehmood ◽  
Muhammad Riaz
Keyword(s):  
Ground Water ◽  
Control Chart ◽  
Physicochemical Parameters ◽  
Auxiliary Information ◽  
Ewma Control Chart

Enhancing the performance of the EWMA control chart for monitoring the process mean using auxiliary information

2018 ◽  
Vol 35 (4) ◽  
pp. 920-933 ◽  
Author(s):  
Nurudeen A. Adegoke ◽  
Saddam Akber Abbasi ◽  
Abdaljbbar B.A. Dawod ◽  
Matthew D.M. Pawley
Keyword(s):  
Control Chart ◽  
Auxiliary Information ◽  
Process Mean ◽  
Ewma Control Chart

PHYSICOCHEMICAL ANALYSIS OF GROUND WATER AND SURFACE WATER IN KOTA REGION, RAJASTHAN, INDIA

2018 ◽  
Vol 24 (1) ◽  
Author(s):  
NITU SINGH ◽  
FATIMA SULTANA
Keyword(s):  
Surface Water ◽  
Ground Water ◽  
Growth And Development ◽  
Physicochemical Parameters ◽  
Total Dissolved Solids ◽  
Physicochemical Analysis ◽  
Total Hardness ◽  
Developing Nation ◽  
The Sustainable Development ◽  
Chloride Sulfate

India is a developing nation and is dependent on its natural resources for growth and development. Water, being one of the vital natural resource, must be used judicially for the sustainable development. Present study focuses on the analysis of physicochemical parameters (pH, Turbidity, Alkalinity, Total Hardness, Total dissolved solids, Conductivity, Chloride, Sulfate, Fluoride contents) of ground water and surface water in Kota City (Rajasthan). The study shows the adverse impact of exploitation and urbanization on water resources of Kota City (Rajasthan). Some physicochemical parameters exceed the desirable limits as defined by WHO and Indian Standards in the selected sites. The level of pollution in ground water and surface water of Kota City is increasing due to urbanization.

scholarly journals Monitoring process mean with a new EWMA control chart

Production ◽  
2011 ◽  
Vol 21 (2) ◽  
pp. 217-222 ◽  
Author(s):  
Yang Su-Fen ◽  
Tsai Wen-Chi ◽  
Huang Tzee-Ming ◽  
Yang Chi-Chin ◽  
Cheng Smiley
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Population Distribution ◽  
Average Run Length ◽  
Process Data ◽  
Ewma Chart ◽  
Ewma Control Chart ◽  
Simple Statistic ◽  
Run Lengths ◽  
Proper Values

In practice, sometimes the process data did not come from a known population distribution. So the commonly used Shewhart variables control charts are not suitable since their performance could not be properly evaluated. In this paper, we propose a new EWMA Control Chart based on a simple statistic to monitor the small mean shifts in the process with non-normal or unknown distributions. The sampling properties of the new monitoring statistic are explored and the average run lengths of the proposed chart are examined. Furthermore, an Arcsine EWMA Chart is proposed since the average run lengths of the Arcsine EWMA Chart are more reasonable than those of the new EWMA Chart. The Arcsine EWMA Chart is recommended if we are concerned with the proper values of the average run length.

Body Welding Quality Control Based on a CUSUM Control Chart

2011 ◽  
Vol 228-229 ◽  
pp. 1080-1084
Author(s):  
Rong Li ◽  
Jing Li ◽  
Jian Liu
Keyword(s):  
Quality Control ◽  
Sample Size ◽  
Control Chart ◽  
Quality Inspection ◽  
Welding Quality ◽  
Ewma Control Chart ◽  
Cusum Control Chart ◽  
Abnormal Variation ◽  
Quality Variation

Aiming at the situation in some Chinese auto companies that the workload of body welding quality inspection is high and the sample size is extremely small, a brand-new CUSUM Control Chart for variance monitoring is proposed in the paper to realize the effective quality control in body welding variance, whose principle is to use variance statistics based on Queensberry transformation Φ-1(G((n-1) St2/σ02)) to monitor infinitely small variances in the process of body welding. Evaluation instance results show that, compared with traditional CUSUM control chart, EWMA control chart and weighted CUSUM control chart, the proposed CUSUM control chart based on variance monitoring is more sensitive to the abnormal variation fluctuation and can detect the abnormity of quality variation earlier.

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