The best surface roughness has been achieved by the lower feed rate and uncoated CBN insert.
📌 3 Key Takeaways
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Objective & Hypothesis:This study focuses on predictive model for Ra and optimization of cutting conditions in high speed hard turning of X40CrMoV5-1 steel by CBN insert.
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Key Findings & Data:Cutting speed, feed rate, depth of cut and coating condition have been considered as cutting parameters.
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Conclusion & Impact:The best surface roughness has been achieved by the lower feed rate and uncoated CBN insert.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Taguchi method · Regression analysis · Hard turning
Abstract
This study focuses on predictive model for Ra and optimization of cutting conditions in high speed hard turning of X40CrMoV5-1 steel by CBN insert. Cutting speed, feed rate, depth of cut and coating condition have been considered as cutting parameters. The experiments have been performed in CNC lathe according to Taguchi L32 orthogonal array. The first order mathematical model for the Ra has been developed with multiple regression analysis. Optimization study with analysis of signal-to-noise (S/N) ratios has indicated that feed rate is the negatively most significant factor for Ra under dry cutting conditions. The best surface roughness has been achieved by the lower feed rate and uncoated CBN insert.
YURTKURAN, H., KORKMAZ, M. E., GÜNAY, M. (2016). MODELLING AND OPTIMIZATION OF THE SURFACE ROUGHNESS IN HIGH SPEED HARD TURNING WITH COATED AND UNCOATED CBN INSERT. Gazi University Journal of Science, Cilt: 29 - Sayı: 4, 987–995. https://ajindex.com/articles/254596
Zhou, J.M., Andersson, M., Stahl, J.E., “Identification of cutting errors in precision hard turning process”, Journal of Materials Processing Technology, 153-154:746–750, (2004).
Grzesik, W., Rech, J., Wanat, T., “Surface finish on hardened bearing steel parts produced by superhard and abrasive tools”, International Journal of Machine Tools and Manufacture, 47:255–262, (2007).
Rech, J., Moisan, A., “Surface integrity in finish hard turning of case-hardened steels”, International Journal of Machine Tools and Manufacture, 43:543–550, (2003).
Bartarya, G., Choudhury, S.K., “State of the art in hard turning”, International Journal of Machine Tools and Manufacture, 53:1–14, (2012).
Shivpuri, R., “Dies and die materials for hot forging”, ASM Handbook, Metalworking: Bulk Forming, USA, (2005).
Xiong, J., Guo, Z., Yang, M., Wan, W., Dong, G., “Tool life and wear of WC–TiC–Co ultrafine cemented carbide during dry cutting of AISI H13 steel”, Ceramics International, 39:337–346, (2013).
Gaitonde, V.N., Karnik, S.R., Figueira, L., Davim, J.P., “Analysis of machinability during hard turning of cold work tool steel (Type: AISI D2)”, Materials and Manufacturing Processes, 24(12):1373-1382, (2009).
Gaitonde, V.N., Karnik, S.R., Figueira, L., Davim, J.P., “Machinability investigations in hard turning of AISI D2 cold work tool steel with conventional and wiper ceramic inserts”, International Journal of Refractory Metals and Hard Materials, 27:754–763, (2009).
Boy, M., Ciftci, I., Gunay, M., Ozhan, F., “Application of the Taguchi method to optimize the cutting conditions in hard turning of a ring bore”, Materials in Technology, 49:765–772, (2015).
Aouici, H., Yallese, M.A., Chaoui, K., Mabrouki, T., Rigal, J.F., “Analysis of surface roughness and cutting force components in hard turning with CBN tool: Prediction model and cutting conditions optimization”, Measurement, 45:344–353, (2012).
Asiltürk, İ., Akkuş, H., “Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method”, Measurement, 44:1697–1704, (2011).
Chinchanikar, S., Choudhury, S.K., “Machining of hardened steel-Experimental investigations, performance modeling and cooling techniques: A review”, International Journal of Machine Tools and Manufacture, 89:95–109, (2015).
Çakır, M.C., Ensarioğlu, C., Demirayak, I., “Mathematical modeling of surface roughness for evaluating the effects of cutting parameters and coating material”, Journal of Materials Processing Technology, 20