Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface Characteristics
In this work, the surface roughness (SR), surface hardness (SH), and the thickness of the affected layer (TL) of the multi-roller flat burnishing process are optimized.The parameter inputs are the tool rotational speed (S), burnishing depth (D), and feed rate (f). The flat burnishing tool having thr...
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2023-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/440432 |
| _version_ | 1797206469383290880 |
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| author | An-Le Van Xuan-Ba Dang Trung-Thanh Nguyen |
| author_facet | An-Le Van Xuan-Ba Dang Trung-Thanh Nguyen |
| author_sort | An-Le Van |
| collection | DOAJ |
| description | In this work, the surface roughness (SR), surface hardness (SH), and the thickness of the affected layer (TL) of the multi-roller flat burnishing process are optimized.The parameter inputs are the tool rotational speed (S), burnishing depth (D), and feed rate (f). The flat burnishing tool having three rollers was utilized to facilitate burnishing trials. The Kriging models of performances are proposed regarding inputs.The CRITIC method and Crow Search Algorithm (CSA) were employed to select weights and optimality. The optimizing outcomes indicated that the optimal values of the S, f, and D were 912 rpm, 150 mm/min, and 0.12 mm, respectively. The improvements in the SR, SH, and TL were 33.3%, 26.9%, and 48.6%, respectively. The SR was primarily influenced by the f, followed by the D and S, respectively. The SH and TL were primarily influenced by the D, followed by the S and f, respectively. The optimal data could be applied to the practical multi-roller burnishing process to improve surface properties for flat surfaces. The Kriging models and CSA could be efficiently utilized to solve complex issues for burnishing operations and other machining processes. |
| first_indexed | 2024-04-24T09:07:31Z |
| format | Article |
| id | doaj.art-c211f6cf6b3e4dd4bac80110020c4340 |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:07:31Z |
| publishDate | 2023-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-c211f6cf6b3e4dd4bac80110020c43402024-04-15T18:42:54ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392023-01-013041166117410.17559/TV-20230103000078Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface CharacteristicsAn-Le Van0Xuan-Ba Dang1Trung-Thanh Nguyen2Faculty of Engineering and Technology, Nguyen Tat Thanh University, 300A Nguyen Tat Thanh Street, Ward 13, District 4, Ho Chi Minh City 70000, VietnamDepartment of Automatic Control, Ho Chi Minh City University of Technology and Education, No. 1 Vo Van Ngan Street, Linh Chieu Ward, Thu Duc City, Ho Chi Minh City 70000, VietnamFaculty of Mechanical Engineering, Le Quy Don Technical University, 236 Hoang Quoc Viet, Ha Noi 100000, VietnamIn this work, the surface roughness (SR), surface hardness (SH), and the thickness of the affected layer (TL) of the multi-roller flat burnishing process are optimized.The parameter inputs are the tool rotational speed (S), burnishing depth (D), and feed rate (f). The flat burnishing tool having three rollers was utilized to facilitate burnishing trials. The Kriging models of performances are proposed regarding inputs.The CRITIC method and Crow Search Algorithm (CSA) were employed to select weights and optimality. The optimizing outcomes indicated that the optimal values of the S, f, and D were 912 rpm, 150 mm/min, and 0.12 mm, respectively. The improvements in the SR, SH, and TL were 33.3%, 26.9%, and 48.6%, respectively. The SR was primarily influenced by the f, followed by the D and S, respectively. The SH and TL were primarily influenced by the D, followed by the S and f, respectively. The optimal data could be applied to the practical multi-roller burnishing process to improve surface properties for flat surfaces. The Kriging models and CSA could be efficiently utilized to solve complex issues for burnishing operations and other machining processes.https://hrcak.srce.hr/file/440432affected layerhardnesskriging modelmulti-roller flat burnishingroughness |
| spellingShingle | An-Le Van Xuan-Ba Dang Trung-Thanh Nguyen Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface Characteristics Tehnički Vjesnik affected layer hardness kriging model multi-roller flat burnishing roughness |
| title | Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface Characteristics |
| title_full | Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface Characteristics |
| title_fullStr | Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface Characteristics |
| title_full_unstemmed | Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface Characteristics |
| title_short | Multi-Response Optimization of the Flat Burnishing Process with a High-Stiffness Tool in terms of Surface Characteristics |
| title_sort | multi response optimization of the flat burnishing process with a high stiffness tool in terms of surface characteristics |
| topic | affected layer hardness kriging model multi-roller flat burnishing roughness |
| url | https://hrcak.srce.hr/file/440432 |
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