Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr Formation
This research presents a study of biodegradable-cutting fluid made by 85 wt. (%) jasmine oil and 15 wt. (%) organic petroleum-based additive as a green substitute for conventional oils in drilling AA 5052-H32 aluminium alloy. Response Surface Methodology (RSM) was applied to investigate the factors...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | International Journal of Sustainable Engineering |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19397038.2025.2538863 |
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| _version_ | 1849402493188964352 |
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| author | Muhammad Yasir Mubashir Gulzar Muhammad Saad Khan Alexis Mounge Nanimina Imtiaz Ali Shahid Iqbal |
| author_facet | Muhammad Yasir Mubashir Gulzar Muhammad Saad Khan Alexis Mounge Nanimina Imtiaz Ali Shahid Iqbal |
| author_sort | Muhammad Yasir |
| collection | DOAJ |
| description | This research presents a study of biodegradable-cutting fluid made by 85 wt. (%) jasmine oil and 15 wt. (%) organic petroleum-based additive as a green substitute for conventional oils in drilling AA 5052-H32 aluminium alloy. Response Surface Methodology (RSM) was applied to investigate the factors of spindle speed and feed rate on surface quality, burr formation and temperature across three lubrication situations: dry, 90–10% and 80–20% water-to-oil mix. Results show that a surface roughness of 7.3 µm at 6370 rpm and 2867 mm/min under 80–20% and retraction rate. This lubrication regime had the smallest amount of burr height of 0.07 mm as the most conducive cooling minimum temperature of 33.8°C. In addition, machine learning models are introduced to predict surface roughness that the Gaussian Process Regression (GPR) model yields the best prediction accuracy. Additionally, state-of-the-art machine learning models were applied to the experimental data to optimise the drilling process. The Optimized Gaussian Process Regression (OGPR) model showed the highest accuracy (R2 = 0.86, RMSE = 1.33, MAE = 1.12), followed by the WNN model (R2 = 0.89), while linear regression performed the worst. These results highlight the potential of ML models in enhancing machining efficiency and sustainability in drilling. |
| format | Article |
| id | doaj-art-97ff9d4a88254fb98e313bb19aab6dd4 |
| institution | Kabale University |
| issn | 1939-7038 1939-7046 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Sustainable Engineering |
| spelling | doaj-art-97ff9d4a88254fb98e313bb19aab6dd42025-08-20T03:37:31ZengTaylor & Francis GroupInternational Journal of Sustainable Engineering1939-70381939-70462025-12-0118110.1080/19397038.2025.2538863Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr FormationMuhammad Yasir0Mubashir Gulzar1Muhammad Saad Khan2Alexis Mounge Nanimina3Imtiaz Ali4Shahid Iqbal5Department of Mechanical Engineering, Wah Engineering College, University of Wah, Wah Cantt, PakistanDepartment of Mechanical Engineering, University of Engineering and Technology Taxila, Taxila, PakistanInterdisciplinary Research Center for membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran, Saudi ArabiaDépartement de génie mécanique, Institut Nationale Supérieur des Sciences et Techniques d’Abéché, Abéché, ChadDepartment of Petroleum and Gas Engineering, BUITEMS, Quetta, PakistanDepartment of Mechanical Engineering, Wah Engineering College, University of Wah, Wah Cantt, PakistanThis research presents a study of biodegradable-cutting fluid made by 85 wt. (%) jasmine oil and 15 wt. (%) organic petroleum-based additive as a green substitute for conventional oils in drilling AA 5052-H32 aluminium alloy. Response Surface Methodology (RSM) was applied to investigate the factors of spindle speed and feed rate on surface quality, burr formation and temperature across three lubrication situations: dry, 90–10% and 80–20% water-to-oil mix. Results show that a surface roughness of 7.3 µm at 6370 rpm and 2867 mm/min under 80–20% and retraction rate. This lubrication regime had the smallest amount of burr height of 0.07 mm as the most conducive cooling minimum temperature of 33.8°C. In addition, machine learning models are introduced to predict surface roughness that the Gaussian Process Regression (GPR) model yields the best prediction accuracy. Additionally, state-of-the-art machine learning models were applied to the experimental data to optimise the drilling process. The Optimized Gaussian Process Regression (OGPR) model showed the highest accuracy (R2 = 0.86, RMSE = 1.33, MAE = 1.12), followed by the WNN model (R2 = 0.89), while linear regression performed the worst. These results highlight the potential of ML models in enhancing machining efficiency and sustainability in drilling.https://www.tandfonline.com/doi/10.1080/19397038.2025.2538863BiodegradableAA 5052-H32 alloymachine learninglubrication |
| spellingShingle | Muhammad Yasir Mubashir Gulzar Muhammad Saad Khan Alexis Mounge Nanimina Imtiaz Ali Shahid Iqbal Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr Formation International Journal of Sustainable Engineering Biodegradable AA 5052-H32 alloy machine learning lubrication |
| title | Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr Formation |
| title_full | Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr Formation |
| title_fullStr | Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr Formation |
| title_full_unstemmed | Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr Formation |
| title_short | Eco-friendly drilling of AA 5052-H32 Alloy: influence of jasmine-based cutting fluid on surface quality and burr Formation |
| title_sort | eco friendly drilling of aa 5052 h32 alloy influence of jasmine based cutting fluid on surface quality and burr formation |
| topic | Biodegradable AA 5052-H32 alloy machine learning lubrication |
| url | https://www.tandfonline.com/doi/10.1080/19397038.2025.2538863 |
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