Using Multivariate Statistical Quality Control Models to Monitor the Quality of Drinking Water in Khan Younis Governorate - Palestine
| المصدر: | المجلة العربية للجودة والتميز |
|---|---|
| الناشر: | مركز الوراق للدراسات والأبحاث |
| المؤلف الرئيسي: | Al-Telbany, Shady Ismail (Author) |
| مؤلفين آخرين: | Ashour, Mohammed Fayez (Co-Author) |
| المجلد/العدد: | مج2, ع2 |
| محكمة: | نعم |
| الدولة: |
الأردن |
| التاريخ الميلادي: |
2015
|
| الشهر: | مايو |
| الصفحات: | 5 - 32 |
| ISSN: |
2521-9294 |
| رقم MD: | 793173 |
| نوع المحتوى: | بحوث ومقالات |
| اللغة: | الإنجليزية |
| قواعد المعلومات: | EcoLink |
| مواضيع: | |
| رابط المحتوى: |
عدد مرات التحميل
4
| المستخلص: |
Groundwater is one of the most precious natural resources in the Gaza Strip as it is the only source of drinking water for the majority of the population. So aim of this study is to evaluate the statistical methods that are used to monitor the quality of drinking water in order to suggest the best statistical models that are used in monitoring and detecting small changes to avoid diseases that may be caused by the problem of water pollution. Our data set were taken for several readings of groundwater wells from Khan Younis governorate for three variables which is the major chemical components of drinking water, which is mainly in judging the quality of drinking water, namely: (Chloride (CL), nitrate (N03), total dissolved salts in water (TDS) ), during period from 1987 to 2012. In this study, univariate control models (Shewhart, EWMA, CUSUM) were applied to the same data set, then make a comparison between three models but was reached that univariate control models have not achieved good control in the detection of small changes, as well as when we resort to explain the problem of variable we need to read and interpret more than one model ,so it has been applied multivariate control models ( Hotelling, MEWMA, MCUSUM) on the same data set and found that it is more sensitive in detecting small changes from than univariate control models, because it give one explanation and one read for more than one variable, then make a comparison between the three types to find the best control model to monitor the quality of drinking water and detect small changes. It was concluded that the MCUSUM model is the best and fastest in achieving better quality control and detect small changes to monitor the quality of drinking water. |
|---|---|
| ISSN: |
2521-9294 |
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