Analysis of the Effect of Cutting Variables against Surface Hardness
Abstract
Indonesia is one of the developing countries and is actively pioneering development, especially development in the industrial sector. The industry that is quite developed at this time is the manufacturing industry which produces a finished product that can be directly used by consumers. These products are expected to have a high enough quality level so that they can compete in the market. To support this quality, one of the factors is to pay attention to the level of precision of the workpiece in this case is the level of surface roughness of the object or product produced. The surface roughness value is obtained from the tests carried out on the product which has an average surface value (Ra) and a maximum roughness value (Ry). To achieve the desired roughness value, it is necessary to make improvements in metal forming work. In the variable cutting with variations in cutting speed, it is said that the cutting speed on work with smaller diameter objects should use a high cutting speed. Feeding thickness that is too large can cause high surface roughness values and high rotation at low cutting speeds to produce a smooth surface but takes a long time. With the selection of the speed of ingestion that varies for the price of the ingestion speed of 43.52 m/minute, the surface roughness value is 6.78 m, the speed is 48.32 m/minute, the surface roughness value is 3.64 m and the ingestion speed is 59.25 m. /min the surface roughness value is 6.14 m. Meanwhile, for the infeed thickness which varies for a feed thickness of 1.2 mm, the surface roughness value is 4.06 m; a feed thickness of 2.4 mm obtained a surface roughness value of 27.82 um and a feed thickness of 3.2 mm obtained a surface roughness value of 7.02 m.
Keywords
Full Text:
PDFReferences
Aouici, H., Yallese, M. A., Chaoui, K., Mabrouki, T., & Rigal, J. F. (2012). Analysis of surface roughness and cutting force components in hard turning with CBN tool: Prediction model and cutting conditions optimization. Measurement, 45(3), 344-353.
Diniardi, E., Ramadhan, A. I., Mubarok, R., & Basri, H. (2015). Analysis of mechanical properties connecting rod bolts outboard motor FT50CEHD. International Journal of Applied Science and Engineering Research, 4(5), 665-670.
Yudistirani, S. A., Mahmud, K. H., & Diniardi, E. (2021). Stamping Disability Analysis on Material SPC 270 E. Journal of Applied Sciences and Advanced Technology, 3(3), 75-80.
Özel, T., Hsu, T. K., & Zeren, E. (2005). Effects of cutting edge geometry, workpiece hardness, feed rate and cutting speed on surface roughness and forces in finish turning of hardened AISI H13 steel. The International Journal of Advanced Manufacturing Technology, 25(3), 262-269.
Mahmud, K. H., Yudistirani, S. A., Diniardi, E., & Ramadhan, A. I. (2020). Hardness Analysis of Bearing on Heat Treatment Process. Journal of Applied Sciences and Advanced Technology, 2(3), 59-64.
Dureja, J. S., Gupta, V. K., Sharma, V. S., & Dogra, M. (2009). Design optimization of cutting conditions and analysis of their effect on tool wear and surface roughness during hard turning of AISI-H11 steel with a coated—mixed ceramic tool. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 223(11), 1441-1453.
Diniardi, E., Nelfiyanti, N., Mahmud, K. H., Basri, H., & Ramadhan, A. I. (2019). Analysis of the Tensile Strength of Composite Material from Fiber Bags. Journal of Applied Sciences and Advanced Technology, 2(2), 39-48.
Rahardja, I. B., Rahdiana, N., Mulyadi, D., Al Afghani, A., & Ramadhan, A. I. (2020). Analisis Pengaruh Radius Bending Pada Proses Bending Menggunakan Pelat Spcc-Sd Terhadap Perubahan Struktur Mikro. Jurnal Teknik Mesin Mechanical Xplore, 1(1), 1-10.
Zębala, W., & Kowalczyk, R. (2015). Estimating the effect of cutting data on surface roughness and cutting force during WC-Co turning with PCD tool using Taguchi design and ANOVA analysis. The International Journal of Advanced Manufacturing Technology, 77(9-12), 2241-2256.
Sharma, V. S., Dhiman, S., Sehgal, R., & Sharma, S. K. (2008). Estimation of cutting forces and surface roughness for hard turning using neural networks. Journal of intelligent Manufacturing, 19(4), 473-483.
Diniardi, E., Setiawan, B., & Ramadhan, A. I. (2019). Fatigue Analysis Aluminium 6063-TF on the Rotary Bending Testing Machine. Journal of Applied Sciences and Advanced Technology, 2(1), 7-12.
Mia, M., & Dhar, N. R. (2017). Optimization of surface roughness and cutting temperature in high-pressure coolant-assisted hard turning using Taguchi method. The International Journal of Advanced Manufacturing Technology, 88(1-4), 739-753.
Azizi, M. W., Belhadi, S., Yallese, M. A., Mabrouki, T., & Rigal, J. F. (2012). Surface roughness and cutting forces modeling for optimization of machining condition in finish hard turning of AISI 52100 steel. Journal of mechanical science and technology, 26(12), 4105-4114.
Rao, K. V., Murthy, B. S. N., & Rao, N. M. (2013). Cutting tool condition monitoring by analyzing surface roughness, work piece vibration and volume of metal removed for AISI 1040 steel in boring. Measurement, 46(10), 4075-4084.
Zhang, J. Z., Chen, J. C., & Kirby, E. D. (2007). Surface roughness optimization in an end-milling operation using the Taguchi design method. Journal of materials processing technology, 184(1-3), 233-239.
Khorasani, A. M., Yazdi, M. R. S., & Safizadeh, M. S. (2012). Analysis of machining parameters effects on surface roughness: a review. International Journal of Computational Materials Science and Surface Engineering, 5(1), 68-84.
DOI: https://doi.org/10.24853/jasat.3.3.81-88
Refbacks
- There are currently no refbacks.
Copyright of Journal of Applied Sciences and Advanced Technology (JASAT)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License