Optimization on milling machining performances of AISI D2 steel using Taguchi method
Surface integrity and tool wear is important to determine the quality of machine surface in order to achieve optimum cutting parameter. This project was conducted to study the optimum of cutting parameters on tool wear and surface roughness using AISI D2 steel under dry milling process. The cutting...
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my.utem.eprints.269622023-09-14T14:36:18Z http://eprints.utem.edu.my/id/eprint/26962/ Optimization on milling machining performances of AISI D2 steel using Taguchi method Ismail, Riduan T Technology (General) TJ Mechanical engineering and machinery Surface integrity and tool wear is important to determine the quality of machine surface in order to achieve optimum cutting parameter. This project was conducted to study the optimum of cutting parameters on tool wear and surface roughness using AISI D2 steel under dry milling process. The cutting tool that has been selected was uncoated carbides end mill and the size of the AISI D2 steel is 100 mm x 60 mm x 20 mm. Deckel Maho DMU 60 CNC Milling machine was utilized in this project to remove the surface of material. The main controllable milling parameters that have been investigated in this project were cutting speed, feed rate and depth of cut. The machining parameters used in this experiment were cutting speed (50 m/min, 70 m/min and 90 m/min), feed rate (0.05 mm/rev, 0.075 mm/rev and 0.1 mm/rev) and depth of cut (0.1mm, 0.3mm and 0.5 mm). In this experiment, Taguchi method is used to obtain the optimum parameters via Minitab 17 software. Mitutoyo surface roughness tester was used to determine the average of surface roughness. The tool wear rate of the cutting tool is analysed using the stereo microscope. Analysis was performed using experimental result and ANOVA. The effect of dry machining condition on surface roughness and tool wear of the workpiece is also analysed. Based on the analysis, the optimum cutting parameter to get the minimum surface roughness were cutting speed (70 m/min), feed rate (0.05 mm/rev) and depth of cut (0.5 mm), while the optimum cutting parameter to get the minimum tool wear were cutting speed (50 m/min), feed rate (0.05 mm/rev) and depth of cut (0.1 mm). It shows that the cutting speed is the most influence parameter that contributed to the highest effect of surface roughness and tool wear followed by the feed rate and depth of cut. 2020 Thesis NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/26962/1/Optimization%20on%20milling%20machining%20performances%20of%20AISI%20D2%20steel%20using%20Taguchi%20method.pdf text en http://eprints.utem.edu.my/id/eprint/26962/2/Optimization%20on%20milling%20machining%20performances%20of%20AISI%20D2%20steel%20using%20Taguchi%20method.pdf Ismail, Riduan (2020) Optimization on milling machining performances of AISI D2 steel using Taguchi method. Masters thesis, Universiti Teknikal Malaysia Melaka. https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=121710 |
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T Technology (General) TJ Mechanical engineering and machinery Ismail, Riduan Optimization on milling machining performances of AISI D2 steel using Taguchi method |
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Surface integrity and tool wear is important to determine the quality of machine surface in order to achieve optimum cutting parameter. This project was conducted to study the optimum of cutting parameters on tool wear and surface roughness using AISI D2 steel under dry milling process. The cutting tool that has been selected was uncoated carbides end mill and the size of the AISI D2 steel is 100 mm x 60 mm x 20 mm. Deckel Maho DMU 60 CNC Milling machine was utilized in this project to remove the surface of material. The main controllable milling parameters that have been investigated in this project were cutting speed, feed rate and depth of cut. The machining parameters used in this experiment were cutting speed (50 m/min, 70 m/min and 90 m/min), feed rate (0.05 mm/rev, 0.075 mm/rev and 0.1 mm/rev) and depth of cut (0.1mm, 0.3mm and 0.5 mm). In this experiment, Taguchi method is used to obtain the optimum parameters via Minitab 17 software. Mitutoyo surface roughness tester was used to determine the average of surface roughness. The tool wear rate of the cutting tool is analysed using the stereo microscope. Analysis was performed using experimental result and ANOVA. The effect of dry machining condition on surface roughness and tool wear of the workpiece is also analysed. Based on the analysis, the optimum cutting parameter to get the minimum surface roughness were cutting speed (70 m/min), feed rate (0.05 mm/rev) and depth of cut (0.5 mm), while the optimum cutting parameter to get the minimum tool wear were cutting speed (50 m/min), feed rate (0.05 mm/rev) and depth of cut (0.1 mm). It shows that the cutting speed is the most influence parameter that contributed to the highest effect of surface roughness and tool wear followed by the feed rate and depth of cut. |
format |
Thesis |
author |
Ismail, Riduan |
author_facet |
Ismail, Riduan |
author_sort |
Ismail, Riduan |
title |
Optimization on milling machining performances of AISI D2 steel using Taguchi method |
title_short |
Optimization on milling machining performances of AISI D2 steel using Taguchi method |
title_full |
Optimization on milling machining performances of AISI D2 steel using Taguchi method |
title_fullStr |
Optimization on milling machining performances of AISI D2 steel using Taguchi method |
title_full_unstemmed |
Optimization on milling machining performances of AISI D2 steel using Taguchi method |
title_sort |
optimization on milling machining performances of aisi d2 steel using taguchi method |
publishDate |
2020 |
url |
http://eprints.utem.edu.my/id/eprint/26962/1/Optimization%20on%20milling%20machining%20performances%20of%20AISI%20D2%20steel%20using%20Taguchi%20method.pdf http://eprints.utem.edu.my/id/eprint/26962/2/Optimization%20on%20milling%20machining%20performances%20of%20AISI%20D2%20steel%20using%20Taguchi%20method.pdf http://eprints.utem.edu.my/id/eprint/26962/ https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=121710 |
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