The Influence Of Work Surface Roughness Caused By Fraising Machined With HSS Chies

Aljufri Aljufri, Muhammad Nuzan Rizki, Syarifah Akmal, Sri Mutia, Farhan Wafi Rambe

Abstract


The development of production techniques is required to produce good products that have standards for the products produced, both in terms of profile shape, size precision, surface roughness, hardness, material flexibility, and others that comply with standards. The surface roughness of a product can affect its functions, such as its level of precision and ability to accept loads. This research aims to find out how much influence cutting speed and depth of cut have on surface roughness with variations in cutting speed parameters of 21 meters/minute and 26 meters/minute and for AISI 4140 steel cutting speed parameters of 12 meters/minute and 17 meters/minute and cutting depths of 0.1 mm and 0.3 mm on four types of steel with End Mill cutting blades made from High-Speed Steel with a total of 4 flute cutting blades. Next, surface roughness testing and analysis of variance were carried out to determine the influence of parameters on surface roughness. The results obtained were that the largest average surface roughness, namely Ra = 5.33 µm, occurred on AISI 4140 steel at a cutting speed of 12 m/min with a cutting depth of 0.3 mm. Meanwhile, the smallest average surface roughness, namely Ra = 0.91 µm, occurred on AISI 1045 steel at a cutting speed of 21 m/min with a cutting depth of 0.1 mm. Next, an analysis of the variance method was also carried out with the following results: cutting speed only affected S45C steel because the value of Fcount>Ftable (13.18107506 > 5.32). The depth of cut does not have a significant effect on surface roughness on all types of steel because of the comparison results Fcount<Ftable. The interaction of cutting speed and cutting depth does not affect surface roughness because the comparison shows that Fcount <Ftable for all types of steel.

Keywords


surface roughness; cutting speed; cutting depth; analysis of variance

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References


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DOI: https://doi.org/10.24853/jasat.6.2.49-56

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