Surface Roughness Modeling of Hard Turning 080A67 Steel
Surface roughness is an important parameter to evaluate the quality of a machining process in mechanical manufacturing. The construction of a surface roughness model of a machining process is the basis for predicting surface roughness corresponding to each certain case. This paper presents the const...
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| Format: | Article |
| Language: | English |
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D. G. Pylarinos
2023-06-01
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| Series: | Engineering, Technology & Applied Science Research |
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| Online Access: | https://etasr.com/index.php/ETASR/article/view/5790 |
| _version_ | 1797694803396263936 |
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| author | Bui Thanh Danh Nguyen Van Cuong |
| author_facet | Bui Thanh Danh Nguyen Van Cuong |
| author_sort | Bui Thanh Danh |
| collection | DOAJ |
| description | Surface roughness is an important parameter to evaluate the quality of a machining process in mechanical manufacturing. The construction of a surface roughness model of a machining process is the basis for predicting surface roughness corresponding to each certain case. This paper presents the construction of a surface roughness model in 080A67 steel turning. An experimental process was carried out with a total of 15 experiments, designed according to the Box-Behnken matrix. The cutting speed, feed rate, and cutting depth were changed in each experiment, and surface roughness values were measured to build a model that showed the mathematical relationship between surface roughness and the three cutting parameters. A second surface roughness model was also constructed using the Box-Cox transformation. The accuracy of these two models was compared through five coefficients: R2, R2(pred), R2(adj), Percentage Absolute Error (PAE), and Percentage Square Error (PSE). The results showed that all these coefficients of the model using the Box-Cox transformation were better than those of the first one. In detail, the values of R2, R2(pred), R2(Adj), PAE, and PSE of the first model were 94.55%, 12.79%, 84.74%, 8.79%, and 1.42%, while for the second model were 99.09%, 85.42%, 97.44%, 2.26%, and 0.18%, respectively, showing that the accuracy of the surface roughness model was improved by using the Box-Cox transformation.
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| first_indexed | 2024-03-12T03:02:05Z |
| format | Article |
| id | doaj.art-60759e874b3c4dbf9f48c5c7286f1251 |
| institution | Directory Open Access Journal |
| issn | 2241-4487 1792-8036 |
| language | English |
| last_indexed | 2024-03-12T03:02:05Z |
| publishDate | 2023-06-01 |
| publisher | D. G. Pylarinos |
| record_format | Article |
| series | Engineering, Technology & Applied Science Research |
| spelling | doaj.art-60759e874b3c4dbf9f48c5c7286f12512023-09-03T14:37:31ZengD. G. PylarinosEngineering, Technology & Applied Science Research2241-44871792-80362023-06-0113310.48084/etasr.5790Surface Roughness Modeling of Hard Turning 080A67 SteelBui Thanh Danh0Nguyen Van Cuong1Faculty of Mechanical Engineering, University of Transport and Communications, VietnamFaculty of Mechanical Engineering, University of Transport and Communications, VietnamSurface roughness is an important parameter to evaluate the quality of a machining process in mechanical manufacturing. The construction of a surface roughness model of a machining process is the basis for predicting surface roughness corresponding to each certain case. This paper presents the construction of a surface roughness model in 080A67 steel turning. An experimental process was carried out with a total of 15 experiments, designed according to the Box-Behnken matrix. The cutting speed, feed rate, and cutting depth were changed in each experiment, and surface roughness values were measured to build a model that showed the mathematical relationship between surface roughness and the three cutting parameters. A second surface roughness model was also constructed using the Box-Cox transformation. The accuracy of these two models was compared through five coefficients: R2, R2(pred), R2(adj), Percentage Absolute Error (PAE), and Percentage Square Error (PSE). The results showed that all these coefficients of the model using the Box-Cox transformation were better than those of the first one. In detail, the values of R2, R2(pred), R2(Adj), PAE, and PSE of the first model were 94.55%, 12.79%, 84.74%, 8.79%, and 1.42%, while for the second model were 99.09%, 85.42%, 97.44%, 2.26%, and 0.18%, respectively, showing that the accuracy of the surface roughness model was improved by using the Box-Cox transformation. https://etasr.com/index.php/ETASR/article/view/5790080A67 steelsurface roughnessBox-Cox transformationhard turning |
| spellingShingle | Bui Thanh Danh Nguyen Van Cuong Surface Roughness Modeling of Hard Turning 080A67 Steel Engineering, Technology & Applied Science Research 080A67 steel surface roughness Box-Cox transformation hard turning |
| title | Surface Roughness Modeling of Hard Turning 080A67 Steel |
| title_full | Surface Roughness Modeling of Hard Turning 080A67 Steel |
| title_fullStr | Surface Roughness Modeling of Hard Turning 080A67 Steel |
| title_full_unstemmed | Surface Roughness Modeling of Hard Turning 080A67 Steel |
| title_short | Surface Roughness Modeling of Hard Turning 080A67 Steel |
| title_sort | surface roughness modeling of hard turning 080a67 steel |
| topic | 080A67 steel surface roughness Box-Cox transformation hard turning |
| url | https://etasr.com/index.php/ETASR/article/view/5790 |
| work_keys_str_mv | AT buithanhdanh surfaceroughnessmodelingofhardturning080a67steel AT nguyenvancuong surfaceroughnessmodelingofhardturning080a67steel |