Optimization of tool life and surface roughness for hypereutectic Al - si alloys in face milling / Kamal Othman...[et al.]

machining processes for automotive components. This study intends to investigate the machining parameters affecting the machinability of hypereutectic Al-Si alloys in the context of surface roughness and tool life via a DLC coated face milling cutter inserted under dry cutting conditions. The machin...

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Main Authors: Othman, Kamal (Author), Abdul Ghani, Jaharah (Author), Juri, Afifah (Author), Ruslan Mohd, Mohd Shahfizal (Author), Kassim, Shahir (Author), Che Haron, Che Hassan (Author)
Format: Book
Published: Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM), 2020.
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Summary:machining processes for automotive components. This study intends to investigate the machining parameters affecting the machinability of hypereutectic Al-Si alloys in the context of surface roughness and tool life via a DLC coated face milling cutter inserted under dry cutting conditions. The machining parameters used in this study were cutting speeds of 250 m/min and 350 m/min, feed rates of 0.02 mm/tooth and 0.04 mm/tooth, and a constant depth of cut of 0.3 mm. The orthogonal full factorial (2³) method was used for the experimental trials. A commercial software called Minitab 17 was used to generate the analysis of variance (ANOVA) and the mathematical prediction model for each machining response. The experimental results confirmed that an excellent surface finish was achieved with a value of as low as 0.140 μm, while the highest value for tool life of 105.47 minute was realized with face milled aluminium alloy A390. From the analyses, it was confirmed that the feed rate is the most significant machining factor affecting surface roughness, while in the case of tool life; cutting speed is the most influential machining factor. The main effect plot showed that the optimum cutting condition for realizing low surface roughness and longer tool life is at 250 m/min, a feed rate of 0.02 mm/tooth, and radial depth of cut 12.5 mm. The prediction model for surface roughness and tool life was developed and reported low percentage errors.
Item Description:https://ir.uitm.edu.my/id/eprint/36498/1/36498.pdf