A parametric bootstrap control chart for Lindley Geometric percentiles.
Control charts are vital for quality control and process monitoring, helping businesses identify variations in production. Traditional control charts, like Shewhart charts, may not work well for skewed distributions, such as the Lindley geometric distribution (LG). This study introduces a new contro...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316449 |
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| author | Muthanna Ali Hussein Al-Lami Hossein Jabbari Khamnei Ali Akbar Heydari |
| author_facet | Muthanna Ali Hussein Al-Lami Hossein Jabbari Khamnei Ali Akbar Heydari |
| author_sort | Muthanna Ali Hussein Al-Lami |
| collection | DOAJ |
| description | Control charts are vital for quality control and process monitoring, helping businesses identify variations in production. Traditional control charts, like Shewhart charts, may not work well for skewed distributions, such as the Lindley geometric distribution (LG). This study introduces a new control chart that uses parametric bootstrap techniques to monitor percentiles of the LG distribution, providing a more effective quality control method. The LG distribution is useful for modeling material strength and failures, especially in structural design, where lower percentiles indicate reduced tensile strength. We conducted extensive simulations to assess the proposed control chart's effectiveness, considering various distribution parameters, percentile values, Type I error rates, and sample sizes. Our findings highlight how subgroup size, percentiles, and significance levels affect control limits, stressing the need for careful parameter selection in monitoring processes. The results show that the new control chart is highly sensitive to changes in LG distribution parameters and performs consistently across different percentiles. This suggests its practical relevance and robustness for industrial applications in quality control. Future research should explore its performance in real-world production settings to confirm its efficiency and reliability. |
| format | Article |
| id | doaj-art-c883274fe12b4c398044ad0530cbfecf |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-c883274fe12b4c398044ad0530cbfecf2025-02-12T05:30:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031644910.1371/journal.pone.0316449A parametric bootstrap control chart for Lindley Geometric percentiles.Muthanna Ali Hussein Al-LamiHossein Jabbari KhamneiAli Akbar HeydariControl charts are vital for quality control and process monitoring, helping businesses identify variations in production. Traditional control charts, like Shewhart charts, may not work well for skewed distributions, such as the Lindley geometric distribution (LG). This study introduces a new control chart that uses parametric bootstrap techniques to monitor percentiles of the LG distribution, providing a more effective quality control method. The LG distribution is useful for modeling material strength and failures, especially in structural design, where lower percentiles indicate reduced tensile strength. We conducted extensive simulations to assess the proposed control chart's effectiveness, considering various distribution parameters, percentile values, Type I error rates, and sample sizes. Our findings highlight how subgroup size, percentiles, and significance levels affect control limits, stressing the need for careful parameter selection in monitoring processes. The results show that the new control chart is highly sensitive to changes in LG distribution parameters and performs consistently across different percentiles. This suggests its practical relevance and robustness for industrial applications in quality control. Future research should explore its performance in real-world production settings to confirm its efficiency and reliability.https://doi.org/10.1371/journal.pone.0316449 |
| spellingShingle | Muthanna Ali Hussein Al-Lami Hossein Jabbari Khamnei Ali Akbar Heydari A parametric bootstrap control chart for Lindley Geometric percentiles. PLoS ONE |
| title | A parametric bootstrap control chart for Lindley Geometric percentiles. |
| title_full | A parametric bootstrap control chart for Lindley Geometric percentiles. |
| title_fullStr | A parametric bootstrap control chart for Lindley Geometric percentiles. |
| title_full_unstemmed | A parametric bootstrap control chart for Lindley Geometric percentiles. |
| title_short | A parametric bootstrap control chart for Lindley Geometric percentiles. |
| title_sort | parametric bootstrap control chart for lindley geometric percentiles |
| url | https://doi.org/10.1371/journal.pone.0316449 |
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