Modeling of splat particle splashing data during thermal spraying with the Burr distribution
Splashing of splat particles is one of the most important phenomena in industrial processes such as thermal spray coating. The data relative to the degree of splashing of splats sprayed with a normal angle are commonly characterized by the Weibull distribution function. In this present study, an eff...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Iranian Research Organization for Science and Technology (IROST)
2017-03-01
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| Series: | Journal of Particle Science and Technology |
| Subjects: | |
| Online Access: | http://jpst.irost.ir/article_582_0647ca05d04ec191a43c4d2021645f62.pdf |
| _version_ | 1818759628441255936 |
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| author | Hanieh Panahi Saeid Asadi |
| author_facet | Hanieh Panahi Saeid Asadi |
| author_sort | Hanieh Panahi |
| collection | DOAJ |
| description | Splashing of splat particles is one of the most important phenomena in industrial processes such as thermal spray coating. The data relative to the degree of splashing of splats sprayed with a normal angle are commonly characterized by the Weibull distribution function. In this present study, an effort has been made to show that the Burr distribution is better than the Weibull distribution for presenting the distribution of the degree of splashing. For this purpose, the Burr Type XII distribution and Weibull distribution are compared using different criteria. Furthermore, because of the great importance of statistical prediction of censored data in reducing costs and improving quality of the coating process, we consider different predictors of this data based on a progressively censored sample. For computing the prediction values we obtain the maximum likelihood estimates using the Expectation-Maximization (EM) algorithm. An important implication of the present study is that the Burr Type XII distribution more appropriately described the degree of splashing data. Therefore, the Burr Type XII can be used as an alternative distribution that adequately describes the splashing data and thereby predicts the censored data. |
| first_indexed | 2024-12-18T06:45:45Z |
| format | Article |
| id | doaj.art-99dd1c5366374cb397fe1845347a6dc8 |
| institution | Directory Open Access Journal |
| issn | 2423-4087 2423-4079 |
| language | English |
| last_indexed | 2024-12-18T06:45:45Z |
| publishDate | 2017-03-01 |
| publisher | Iranian Research Organization for Science and Technology (IROST) |
| record_format | Article |
| series | Journal of Particle Science and Technology |
| spelling | doaj.art-99dd1c5366374cb397fe1845347a6dc82022-12-21T21:17:29ZengIranian Research Organization for Science and Technology (IROST)Journal of Particle Science and Technology2423-40872423-40792017-03-0131415010.22104/jpst.2017.2018.1071582Modeling of splat particle splashing data during thermal spraying with the Burr distributionHanieh Panahi0Saeid Asadi1Department of Mathematics and Statistics, Lahijan Branch, Islamic Azad University, Lahijan, IranDepartment of Mechanical Engineering, Payame Noor University (PNU), Tehran, IranSplashing of splat particles is one of the most important phenomena in industrial processes such as thermal spray coating. The data relative to the degree of splashing of splats sprayed with a normal angle are commonly characterized by the Weibull distribution function. In this present study, an effort has been made to show that the Burr distribution is better than the Weibull distribution for presenting the distribution of the degree of splashing. For this purpose, the Burr Type XII distribution and Weibull distribution are compared using different criteria. Furthermore, because of the great importance of statistical prediction of censored data in reducing costs and improving quality of the coating process, we consider different predictors of this data based on a progressively censored sample. For computing the prediction values we obtain the maximum likelihood estimates using the Expectation-Maximization (EM) algorithm. An important implication of the present study is that the Burr Type XII distribution more appropriately described the degree of splashing data. Therefore, the Burr Type XII can be used as an alternative distribution that adequately describes the splashing data and thereby predicts the censored data.http://jpst.irost.ir/article_582_0647ca05d04ec191a43c4d2021645f62.pdfBurr Type XIICensored Datasplat particleSplashingProgressively censoringThermal Spray |
| spellingShingle | Hanieh Panahi Saeid Asadi Modeling of splat particle splashing data during thermal spraying with the Burr distribution Journal of Particle Science and Technology Burr Type XII Censored Data splat particle Splashing Progressively censoring Thermal Spray |
| title | Modeling of splat particle splashing data during thermal spraying with the Burr distribution |
| title_full | Modeling of splat particle splashing data during thermal spraying with the Burr distribution |
| title_fullStr | Modeling of splat particle splashing data during thermal spraying with the Burr distribution |
| title_full_unstemmed | Modeling of splat particle splashing data during thermal spraying with the Burr distribution |
| title_short | Modeling of splat particle splashing data during thermal spraying with the Burr distribution |
| title_sort | modeling of splat particle splashing data during thermal spraying with the burr distribution |
| topic | Burr Type XII Censored Data splat particle Splashing Progressively censoring Thermal Spray |
| url | http://jpst.irost.ir/article_582_0647ca05d04ec191a43c4d2021645f62.pdf |
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