Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys
The optimization of wear rate parameters in metallic alloys using Response Surface Methodology (RSM) has been experimentally performed. The wear rate, a critical factor affecting the durability and performance of metallic components, served as the response parameter, while track diameter, sliding s...
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| Format: | Article |
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College of Engineering of Afe Babalola University, Ado-Ekiti (ABUAD), Ekiti State, Nigeria
2024-07-01
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| Series: | ABUAD Journal of Engineering Research and Development |
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| Online Access: | https://journals.abuad.edu.ng/index.php/ajerd/article/view/498 |
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| author | Blessing Ngozi Goodluck Aliemeke Lucky Charles Peace Omoregie Abdulrazak Momodu Christopher Jerry Emmanuel Akpan |
| author_facet | Blessing Ngozi Goodluck Aliemeke Lucky Charles Peace Omoregie Abdulrazak Momodu Christopher Jerry Emmanuel Akpan |
| author_sort | Blessing Ngozi Goodluck Aliemeke |
| collection | DOAJ |
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The optimization of wear rate parameters in metallic alloys using Response Surface Methodology (RSM) has been experimentally performed. The wear rate, a critical factor affecting the durability and performance of metallic components, served as the response parameter, while track diameter, sliding speed, and mass difference were considered as independent variables. The Central Composite Design (CCD) experimental method systematically explored the response surface and optimizes the wear rate. A mathematical model was developed, revealing a significant p-value of 0.043 in the ANOVA table, indicating the collective influence of the independent variables on wear rate at a significance level of 0.05. Furthermore, the model demonstrates a substantial explanatory power, with R-squared of 69.45% and adjusted R-squared of 51.95%. The p-value calculated to be 0.60 for the statistical Lack of fit indicated a satisfactory model. These findings highlight the effectiveness of RSM in optimizing the experimental input values and offer valuable insights for enhancing the durability and performance of metallic alloys in various industrial applications. The obtained result addresses the problem of uncertainty inherent in optimal levels of input parameters wear experimentation.
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| format | Article |
| id | doaj-art-70e484901f03495bacd676540499b9cb |
| institution | DOAJ |
| issn | 2756-6811 2645-2685 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | College of Engineering of Afe Babalola University, Ado-Ekiti (ABUAD), Ekiti State, Nigeria |
| record_format | Article |
| series | ABUAD Journal of Engineering Research and Development |
| spelling | doaj-art-70e484901f03495bacd676540499b9cb2025-08-20T02:58:19ZengCollege of Engineering of Afe Babalola University, Ado-Ekiti (ABUAD), Ekiti State, NigeriaABUAD Journal of Engineering Research and Development2756-68112645-26852024-07-017210.53982/ajerd.2024.0702.06-j415Response Surface Methodology Optimization of Wear Rate Parameters in Metallic AlloysBlessing Ngozi Goodluck Aliemeke0Lucky Charles1Peace Omoregie2Abdulrazak Momodu3Christopher Jerry4Emmanuel Akpan5Department of Mechanical Engineering, Auchi Polytechnic, NigeriaDepartment of Mechanical Engineering, Auchi Polytechnic, NigeriaDepartment of Mechanical Engineering, Auchi Polytechnic, NigeriaDepartment of Mechanical Engineering, Auchi Polytechnic, NigeriaDepartment of Mechanical Engineering, Auchi Polytechnic, NigeriaDepartment of Mechanical Engineering, Auchi Polytechnic, Nigeria The optimization of wear rate parameters in metallic alloys using Response Surface Methodology (RSM) has been experimentally performed. The wear rate, a critical factor affecting the durability and performance of metallic components, served as the response parameter, while track diameter, sliding speed, and mass difference were considered as independent variables. The Central Composite Design (CCD) experimental method systematically explored the response surface and optimizes the wear rate. A mathematical model was developed, revealing a significant p-value of 0.043 in the ANOVA table, indicating the collective influence of the independent variables on wear rate at a significance level of 0.05. Furthermore, the model demonstrates a substantial explanatory power, with R-squared of 69.45% and adjusted R-squared of 51.95%. The p-value calculated to be 0.60 for the statistical Lack of fit indicated a satisfactory model. These findings highlight the effectiveness of RSM in optimizing the experimental input values and offer valuable insights for enhancing the durability and performance of metallic alloys in various industrial applications. The obtained result addresses the problem of uncertainty inherent in optimal levels of input parameters wear experimentation. https://journals.abuad.edu.ng/index.php/ajerd/article/view/498Response Surface Methodology (RSM)Central Composite Design (CCD)Wear rateANOVAOptimizationp-value |
| spellingShingle | Blessing Ngozi Goodluck Aliemeke Lucky Charles Peace Omoregie Abdulrazak Momodu Christopher Jerry Emmanuel Akpan Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys ABUAD Journal of Engineering Research and Development Response Surface Methodology (RSM) Central Composite Design (CCD) Wear rate ANOVA Optimization p-value |
| title | Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys |
| title_full | Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys |
| title_fullStr | Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys |
| title_full_unstemmed | Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys |
| title_short | Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys |
| title_sort | response surface methodology optimization of wear rate parameters in metallic alloys |
| topic | Response Surface Methodology (RSM) Central Composite Design (CCD) Wear rate ANOVA Optimization p-value |
| url | https://journals.abuad.edu.ng/index.php/ajerd/article/view/498 |
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