A Comparison Between the MEWMA and Mahalanobis Distance Control Chart
Statistical Process Control (SPC) is approaching that uses statistical techniques to monitor the process. The methods of quality control are widely used in controlling any strategy—the widely used control charts. A traditional variable control chart includes three lines: the Centre Line (CL), the Up...
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| Format: | Article |
| Language: | English |
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Sulaimani Polytechnic University
2021-12-01
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| Series: | Kurdistan Journal of Applied Research |
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| Online Access: | https://kjar.spu.edu.iq/index.php/kjar/article/view/643 |
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| author | Kawa Rashid |
| author_facet | Kawa Rashid |
| author_sort | Kawa Rashid |
| collection | DOAJ |
| description | Statistical Process Control (SPC) is approaching that uses statistical techniques to monitor the process. The methods of quality control are widely used in controlling any strategy—the widely used control charts. A traditional variable control chart includes three lines: the Centre Line (CL), the Upper Control Limit (UCL), and the Lower Control Limit (LCL), all of which are represented by numeric values—represented by numeric values. A control chart illustrates the centerline of the average value of the quality feature under investigation.
Depending on numeric observation values, a process is either "in control" or "out of control."
Considering the current, there are no questions regarding the observations and their values during the production process. However, when these observations include human judgments, assessments, and choices, a continuous random variable (xi) of a manufacturing process should be made up of the variable.
The MEWMA and Mahalanobis distance control chart techniques are used when more than one variable is involved.
This paper aims to compare the MEWMA and Mahalanobis distance chart for three compounds for water drinking production in the ALA -Factory in the Sulaimani-Iraq region.
So, linguistic terms can be used instead of the exact value of the continuous random variable. Today, quality control has become one of the most essential techniques for studying all variables to control production or consumption decision factors. Quality control's primary aim is to guarantee that the goods, services, or processes delivered satisfy particular standards and are reliable and satisfactory. The factor's direct approach is based on the product's quality.
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| format | Article |
| id | doaj-art-71906ef523d04350a81a4dea19183b96 |
| institution | Kabale University |
| issn | 2411-7684 2411-7706 |
| language | English |
| publishDate | 2021-12-01 |
| publisher | Sulaimani Polytechnic University |
| record_format | Article |
| series | Kurdistan Journal of Applied Research |
| spelling | doaj-art-71906ef523d04350a81a4dea19183b962025-02-09T20:59:49ZengSulaimani Polytechnic UniversityKurdistan Journal of Applied Research2411-76842411-77062021-12-016210.24017/science.2021.2.9643A Comparison Between the MEWMA and Mahalanobis Distance Control ChartKawa RashidStatistical Process Control (SPC) is approaching that uses statistical techniques to monitor the process. The methods of quality control are widely used in controlling any strategy—the widely used control charts. A traditional variable control chart includes three lines: the Centre Line (CL), the Upper Control Limit (UCL), and the Lower Control Limit (LCL), all of which are represented by numeric values—represented by numeric values. A control chart illustrates the centerline of the average value of the quality feature under investigation. Depending on numeric observation values, a process is either "in control" or "out of control." Considering the current, there are no questions regarding the observations and their values during the production process. However, when these observations include human judgments, assessments, and choices, a continuous random variable (xi) of a manufacturing process should be made up of the variable. The MEWMA and Mahalanobis distance control chart techniques are used when more than one variable is involved. This paper aims to compare the MEWMA and Mahalanobis distance chart for three compounds for water drinking production in the ALA -Factory in the Sulaimani-Iraq region. So, linguistic terms can be used instead of the exact value of the continuous random variable. Today, quality control has become one of the most essential techniques for studying all variables to control production or consumption decision factors. Quality control's primary aim is to guarantee that the goods, services, or processes delivered satisfy particular standards and are reliable and satisfactory. The factor's direct approach is based on the product's quality. https://kjar.spu.edu.iq/index.php/kjar/article/view/643Statistical Process Control (Exponentially Weighted Moving Average-EWMA and Multi Exponentially Weighted Moving Average (MEWMA) chart and Mahalanobis distance |
| spellingShingle | Kawa Rashid A Comparison Between the MEWMA and Mahalanobis Distance Control Chart Kurdistan Journal of Applied Research Statistical Process Control (Exponentially Weighted Moving Average-EWMA and Multi Exponentially Weighted Moving Average (MEWMA) chart and Mahalanobis distance |
| title | A Comparison Between the MEWMA and Mahalanobis Distance Control Chart |
| title_full | A Comparison Between the MEWMA and Mahalanobis Distance Control Chart |
| title_fullStr | A Comparison Between the MEWMA and Mahalanobis Distance Control Chart |
| title_full_unstemmed | A Comparison Between the MEWMA and Mahalanobis Distance Control Chart |
| title_short | A Comparison Between the MEWMA and Mahalanobis Distance Control Chart |
| title_sort | comparison between the mewma and mahalanobis distance control chart |
| topic | Statistical Process Control (Exponentially Weighted Moving Average-EWMA and Multi Exponentially Weighted Moving Average (MEWMA) chart and Mahalanobis distance |
| url | https://kjar.spu.edu.iq/index.php/kjar/article/view/643 |
| work_keys_str_mv | AT kawarashid acomparisonbetweenthemewmaandmahalanobisdistancecontrolchart AT kawarashid comparisonbetweenthemewmaandmahalanobisdistancecontrolchart |